Pay-for-performance (PFP) is considered one of the strongest tools to motivate employees, yet despite its popularity, it can sometimes create stress for workers that results in decreased performance, creativity, and engagement. New research suggests that how employees view their supervisor has a role in determining whether workers view PFP as a motivating challenge, leading them to achieve new heights, or a stressful threat that impacts their work. The authors offer tips for companies and managers on how to best harness the benefits of PFP while addressing some of the ways it can lead to stress

Park, Sanghee; Kong, Dejun “Tony”; Peng, Jian. Research: Pay-for- Performance Doesn’t Have to Stress Workers Out. Harvard Business Review Digital Articles. 10/17/2024, p1-7.

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Yan Liu and Dan Zhang. 2023. . Forthcoming, Management Science.

Consumers often receive a full or partial refund for product returns or service cancellations. Much of the existing literature studies cash refunds, where consumers get their money back minus a fee upon a product return or service cancellation. However, not all refunds are issued in cash. Sometimes consumers receive credit that can be used for future purchases, oftentimes with an expiration term after which the credit is forfeited. We study the optimal design of credit refund policies. Different from models that consider cash refunds, we explicitly model repeated interactions between the seller and consumers over time. We assume that consumers’ valuation for the product/service varies over time, and that there is an exogenous probability for product returns. Several interesting results emerge. First, a credit refund policy facilitates intra-consumer price discrimination for a single type of consumers with stochastic valuation. Second, an optimal policy often involves an intermediate credit expiration term, under which a consumer with a high product valuation always makes a purchase, while a consumer with a low product valuation may be induced to make a purchase as the credit approaches expiration, leading to a demand induction effect. Finally, a credit refund policy can be more profitable than a cash refund policy and can lead to a win-win outcome for both the firm and consumers under certain conditions. We also consider several extensions to check the robustness of our findings.

Leeds professors Manuel Laguna, John Lynch, Russell Cropanzano, Jeff Reuer, Tong Kong and Jeff York have earned a place among the world's most elite and impactful researchers based on standardized citation metrics published by Stanford University. The faculty we among more than 100,000 researchers who were classified into 22 scientific fields and 174 sub-fields according to the standard Science-Metrix classification.

Rui Zhang, Saied Samiedaluie, and Dan Zhang. 2022. . Operations Research, 70(5):2837-2850.

The approximate linear programming approach has received significant attention in the network revenue management literature. A popular approximation in the existing literature is separable piecewise linear (SPL) approximation, which estimates the value of each unit of each resource over time. SPL approximation can be used to construct resource-based bid-price policies. In this paper, we propose a product-based SPL approximation. The coefficients of the product-based SPL approximation can be interpreted as each product’s revenue contribution to the value of each unit of each resource in a given period. We show that the resulting approximate linear program (ALP) admits compact reformulations, like its resource-based counterpart. Furthermore, the new approximation allows us to derive a set of valid inequalities to (i) speed up the computation and (ii) select optimal solutions to construct more effective policies. We conduct an extensive numerical study to illustrate our results. In a set of 192 problem instances, bid-price policies based on the new approximation generate higher expected revenues than resource-based bid-price policies, with an average revenue lift of 0.72% and a maximum revenue lift of 5.3%. In addition, the new approximation can be solved 1.42 times faster than the resource-based approximation and shows better numerical stability. The valid inequalities derived from the new approximation further improve the computational performance and are critical for achieving additional gains in the expected revenue. The policy performance is competitive compared with the dynamic programming decomposition method, which is the strongest heuristic known in the literature.

Yan Liu, Yacheng Sun, and Dan Zhang. 2021. . Operations Research, 69(6): 1823-1841.

We study the effects of redemption hurdles on reward program members’ decision-making and firm profitability. We focus on the popular “Buy X, Get One Free” (BXGO) programs, which set a redemption threshold (X), and possibly an expiration term for the reward. In our model, forward-looking consumers interact with a monopolistic firm, and strategically make purchase and redemption decisions over an infinite time horizon. Our analysis leads to the following results. First, a consumer’s purchase utility and purchase probability increase as her reward point inventory approaches the redemption threshold or expiration. These patterns are consistent with the “point pressure” phenomenon documented in the empirical literature. Second, a redemption threshold alone cannot improve the firm’s profit, unless it is coupled with a finite expiration term, or a positive transaction utility that consumers may derive from reward redemption. Third, setting the optimal redemption threshold requires the program to strike a balance between the effective price paid by consumers and their purchase probabilities. These results have rich managerial implications for effectively designing reward programs.

A Harvard Business Review article summarizing the findings of this paper and can be found .

Leeds professor earns Kahle award for algorithm aimed at improved targeting.

A paper aimed at helping businesses better target consumers through personalized advertising of curated products is this year’s winner of the Kahle Family Research Award at Leeds.

Rico Bumbaca, an assistant professor of marketing at Leeds, is the winner of this distinguished honor, presented to one exceptional faculty research paper published in an elite journal.

“I’m still very new to Leeds, I’m only an assistant professor,” said Prof. Bumbaca, who earned his PhD from the University of California Irvine. “I don’t consider myself to be in the same league as my colleagues, who are brilliant and much more seasoned. I am stunned and humbled by this honor.”

He may be new, but Prof. Bumbaca’s work merits distinction for its potential applications in industry. Alongside researchers from the University of Chicago’s Booth School of Business and the Anderson School of Management at UCLA, he developed an algorithm that quickly scales large data sets to generate highly accurate projections of customers’ wants and desires.

This is a crucial unmet need, as for all the data potential customers are generating, many marketing departments remain unsophisticated when it comes to identifying the right message for the right customer.

Bumbaca and his team describe how this method works in their new paper, “Scalable Target Marketing: Distributed Markov Chain Monte Carlo for Bayesian Hierarchical Models,” which was published in the Journal of Marketing Research in October.

“The method takes advantage of supercomputers by breaking up the data into smaller chunks, processing each chunk in parallel and combining the results to provide very precise estimates of a consumer’s preferences,” Prof. Bumbaca said.

This information about consumers’ preferences can then be used by firms to more accurately target their messaging and increase the likelihood of consumers’ responses to their advertising.

“The key takeaway is that firms can now provide a win-win for their target customers,”

says Bumbaca.

“Customers win by having fewer annoying messages they need to process from firms, and the messages they do receive are spot-on in terms of meeting their needs,” he said. “Firms win by increasing the efficiency of their marketing efforts at a reduced cost, earning larger returns on their smaller marketing budgets.”

The team applied the method for a charitable organization that wants to more efficiently target potential donors. Using their algorithm, they predicted an increase in $1.6 million to $4.2 million in incremental donations per campaign, more than the amount of donations using a traditional statistical method.  

Prof. Bumbaca is already working on other areas related to this research stream. He’s currently investigating a method to calculate the distribution of unique preferences related to a product or service. This is different from target marketing, when you want to know how a particular customer will react to a particular message or product, based on the data she’s generated.

“When you’re looking at a new product line, it’s easy to come up with the two or three biggest segments of your market,” he said. “But with a larger sample size, you may see two or three niche areas you didn’t consider,” opening up potential new markets or applications for a product manager.

Entrepreneurs and startups are increasingly turning to digital platforms nowadays, whether it is about creating a new platform (think Snapchat or TikTok), or providing product offerings and soliciting ideas on an existing platform.

Entrepreneurs and startups are increasingly turning to digital platforms nowadays, whether it is about creating a new platform (think Snapchat or TikTok), or providing product offerings and soliciting ideas on an existing platform. Consider Kickstarter’s platform that features listings of thousands of entrepreneurial projects to connect with the millions of registered backers online, or Apple’s App Store hosting millions of mobile apps published by developers and billions of users of iOS devices. Indeed, digital platforms are now being seen as “semi-regulated” marketplaces that foster innovation and entrepreneurship under the coordination of the platform owner (Kickstarter, Apple). Yet, such coordination is surely easier said than done. Platform owners do not own these product offerings (entrepreneurial projects, apps) or have direct control over their business partners (entrepreneurs, app developers).

So what can a platform owner do to orchestrate the value creation activities of autonomous business partners (in thousands and millions) that are critical to the vibrancy and success of a platform?

This question was the focus of a research paper coauthored by Leeds School’s Strategy & Entrepreneurship professor Tony Tong, in collaboration with two PhD alumni, (currently assistant professor at Tulane University) and (currently assistant professor at the University of Virginia), recently published in the and previously presented at the . The researchers argue that platform owners can use what they call “access control” to shape business partners’ activities.

Specifically, they looked at how such access control in the form of “jailbreaking” shapes app developers’ activities. Apple’s iOS is well-known for adopting a strict gatekeeping policy that controls for what (apps) or who (app develops) have access to the platform. The jailbreak of the iOS is a hacking that exploits loopholes to remove Apple’s built-in restrictions, allowing users to install apps not officially approved by Apple’s App Store. After jailbreaking, many apps that were previously denied by Apple’s App Store can gain access to a sizable number of users of jailbroken iOS devices, exerting a competitive pressure to iOS developers who develop “legit” apps and profit from app sales.

The researchers leveraged the unexpected timing of the jailbreak of iOS 7 in December 2013 to conduct a “natural experiment”. They compared the knowledge sharing activity of iOS app developers (which they consider the treatment group) and the activity of otherwise comparable Android app developers unaffected by the jailbreak (the control group), on StackOverflow.com, an active online forum of software developers. They found that with the jailbreaking, the resulting deficiency in iOS’s gatekeeping—the weakened platform access control—reduced the amount, as well as the quality, of the information shared by iOS app developers. The findings suggest that increased competitive threat—due to the “unauthorized” entry of copycat products into the platform—dampens app developers’ incentives to share knowledge.

In other words, stronger access control, at least in the case of Apple’s iOS, appears beneficial to platform owners, because it facilitates vibrant knowledge sharing among app developers, which should enhance their innovation and product development.

On a broad level, this study highlights that opening platform access too widely to ecosystem partners offering substitutive products can significantly shift the dynamics among them toward a more competitive stance. Such dynamics ultimately shape the success of the platform, and thus are worth paying close attention to, for entrepreneurs and innovators aiming to create a new platform or release their product offerings on an existing platform.

The takeaway?

While openness was often touted as being critical to orchestrating innovation, too much openness—especially to partners with highly similar products or services—may in fact dampen innovation and entrepreneurial activities.

[video:https://youtu.be/7f46X39JzoY]

Michael Porter is an economist, researcher, author, advisor, speaker, and teacher. Throughout his lifetime career at Harvard Business School, he has brought economic theory and strategy concepts to bear on many of the most challenging problems facing corporations, economies and societies, including market competition and company strategy, economic development, the environment, and health care. His extensive research is widely recognized in governments, corporations, NGOs, and academic circles around the globe. His research has received numerous awards, and he is the most cited scholar today in economics and business. 

Harvard Business Review
by Daitian Li, Tony W. Tong, and Yangao Xiao

Tony W. Tong, a professor of strategy & entrepreneurship in the Leeds School of Business, co-authored an article discussing China’s stunning progress in the AI industry. However, according to Tong and his co-authors, the conditions that helped China catch up might also pose a challenge to its future development in AI as the country reaches the innovation frontier. 

A strong sense of self is a positive indicator in the future growth, success and sustainability of entrepreneurial ventures, new research shows. 

A recent study by Leeds Associate Professor of strategy and entrepreneurship, Jeff York and co-authors from the Nottingham University Business School, and from the Warwick Business School, focuses on founders’ personal identity—a characteristic underexplored in current entrepreneurial founders research.

Empirical research has long underscored the association between the success of entrepreneurial ventures and founders’ identities. However, little investigation exists in how a founder’s identity evolves over time.

As leaders of sustainable ventures seek to better understand how they can drive change in their work, the answers may lie in their own behaviors.

Staying true to self

For emerging entrepreneurs, starting a new venture poses unique challenges they learn to tackle in the process. Over time, their decisions and actions shape the organization along with their identity. In many instances, a founder's personal beliefs, the values the hold across all situations, guide their decision-making processes.

In other words, founders often make business decisions based on what they think is right, instead of following the lead of others. 

“Many struggled with the idea of being a “business person” and did not associate themselves as being entrepreneurs. Instead, they had a concept or passion that guided their decision making and shaped their venture over time,”

says York.

“We didn't come from the idea of traditional entrepreneurs…we hadn't been to business school or anything like that.” offered one study participant.

Founders who continue to develop their sense of self through actions that reflect their authenticity can find their way to being comfortable as an entrepreneur, but not if they betray their personal values.

Striking new ground

Unlike previous research, which focuses on comparing a founder’s identity with behaviors established by desirable social norms, the authors designed this study to expand our understanding of founders’ sense of self, values and beliefs.

The study is based on personal interviews with founders over the course of three years and hundreds of hours, complemented with an AI-led qualitative analysis of content sourced from founders’ blogs, organizational brochures, websites, founders’ books and press coverage, among others.

Their findings shed light on how these emerging entrepreneurs viewed themselves.

The authors theorized a process model called Founder Authenticity Work to describe founders’ actions. The model characterizes founders’ actions, decisions and activities over time and how these factors shape their identity.

The researchers agree that further exploration of first-time sustainable entrepreneurs is needed. In particular, there is gap in the study of founders who stay true to themselves, whose self-identity is rooted in their values and beliefs, and how that influences their choice to start impactful entrepreneurial ventures.