Faculty and Research

Linda Argote (Carnegie Mellon, Tepper School of Management)

"Working Alone or Together? Individual Motivation, Group Identification, and the Development of Transactive Memory Systems" Abstract: Although research shows that teams with well-developed transactive memory systems (TMS) outperform teams lacking such memory systems, we know little about how teams develop TMS. In particular, we do not know how individual motivation affects the development of interdependent knowledge structures such as TMS. Using data from management teams engaged in a realistic business simulation, we examine the relationships among individual motivation, TMS, social identity, cohesion, and team performance. We discover that individual motivation to achieve group goals has a negative effect on the development of TMS in teams where both social identity and cohesion are low and do not direct the efforts of team members towards working together. Only when group identification, driven by social identity and cohesion, encourages team members to work together, does individual motivation stimulate the development of interdependent specialized structures of knowledge such as TMS. Moreover, findings show that, as predicted, TMS positively influences team performance. The study extends our understanding of the development of TMS by investigating the effects of motivation and group identification on team knowledge structures and the effects of those knowledge structures on performance.

Keith Sawyer (Washingon University in St. Louis)

"Organizational Learning and Organizational Innovation" Abstract: Organization scholarship is based on a key assumption: that groups and organizations are somehow different from the individuals in them. Otherwise, individual psychology would be capable of providing complete and full explanations of organizational phenomena. For example, scholars who study organizational innovation take it for granted that it involves more than individual creativity. Likewise, scholars of organizational learning assume that it involves more than the learning of individuals in the organization. I use the examples of organizational innovation and organizational learning to explore these questions: What is the relationship between individuals and organizations? Are organizations nothing more than the people in them? How do interactions among people result in emergent group properties? Do these emergent group properties have any causal influence on individuals? These questions are foundational to all social sciences, and they are particularly critical to organizational studies. I draw on data from two studies-interaction in improvisational theater, and the history of technological innovation-to propose a theoretical framework of the relationship between individuals, groups, and organizations.

M. Eric Johnson (Dartmouth)

"Information Risk of Inadvertent Disclosure - An Analysis of File-Sharing Risk in the Financial Supply Chain." Abstract: Firms face many different types of information security risk. Inadvertent disclosure of sensitive business information represents one of the largest classes of recent security breaches. We examine a specific instance of this problem - inadvertent disclosures through peer-to-peer file-sharing networks. We characterize the extent of the security risk for a group of large financial institutions using a direct analysis of leaked documents. We also characterize the threat of loss by examining search patterns in peer-to-peer networks. Our analysis demonstrates both a substantial threat and vulnerability for large financial firms. We find a statistically significant link between leakage and leak sources including the firm employment base and the number of retail accounts. We also find a link between firm visibility and threat activity. Finally, we find that firms with more leaks also experience increased threat.

Lawrence Wein (Stanford)

"Unready for Anthrax." Abstract: We give a brief description of our research on four topics in homeland security and public health: preparedness and response to a bioterror anthrax attack and to a bioterror attack on the food supply, routes of transmission and infection control for pandemic influenza, and biometrics (e.g., fingerprint matching) to prevent terrorists from entering the country. We focus on the modeling, the policy recommendations and the implementation of these recommendations. At the end of the talk, we attempt to draw lessons about policy implementation from these examples and from examples from our other homeland security work, including a bioterror smallpox attack, preventing nuclear weapons from entering the country on a shipping container, preventing nuclear weapons from entering a city, and preventing terrorists from sneaking across the U.S.-Mexico border.

Marvin Lieberman (UCLA Anderson School of Management)

"Industry Learning Environments and the Heterogeneity of Firm Performance" Abstract: Using plant-level data from the entire US manufacturing sector, we characterize inter-industry heterogeneity in rates of learning-by-doing and examine how industry learning rates are connected with firm performance. We find that learning rates vary considerably among industries and are higher in industries with greater R&D, advertising, and capital intensity. Producer concentration increases with the learning rate in a manner suggesting that learning-by-doing has characteristics of an endogenous sunk cost. More importantly, we find that higher rates of learning are associated with wider dispersion of Tobin's /q/ and profitability among firms in the industry. These findings suggest that learning intensity represents an important characteristic of the industry environment that affects market structure and the range of firm performance.

Woodward Yang (Harvard School of Engineering and Applied Sciences)

"The New Economics of Semiconductor Manufacturing." Abstract: Semiconductor manufacturing has been the engine driving the Information Revolution by providing continually more powerful and cheaper computing and communication hardware. Moore's Law is often cited when referring to the clockwork doubling of semiconductor manufacturing technology every 18 months over the past 40 years. The semiconductor industry's continual pursuit of Moore's Law has yielded ever smaller, faster, and cheaper transistors but at the cost of ever more expensive fabrication facilities. There are now clear signs that Moore's Law as the industry has known it for the past 40 years is rapidly coming to an end. Powerful new economic forces are now reshaping the industry as leading semiconductor manufacturers such as Intel, AMD, Texas Instruments, Motorola, TSMC and Samsung struggle to regain profitability and competitiveness. Taking a cue from the automobile industry, we applied some of the lessons of the Toyota Production System (TPS) and were able to demonstrate radical improvement in the manufacturing efficiency of a state-of-the-art semiconductor fab operated by an Integrated Device Manufacturer (IDM) at the forefront of technology and operational excellence. These improvements were realized without any new equipment or change in product design or technical specifications. The implications of these types of changes in the operational management of semiconductor manufacturing are profound and will create new opportunities for growth in the semiconductor industry but along a different vector from Moore's Law.

Rachna Shah (Carlson School of Management)

Paper: Task Uncertainty and Hand-Offs in Inter-Organizational Process Improvement: Analysis of Patient Outcomes in a State-Wide Heart Attack Treatment Program. Seminar Title: "Examining the impact of variability on patient and hospital outcomes" Abstract: Although process analysis research shows that variability reduction leads to superior process and financial performance, we know little about how managers choose from many different activities constituting a process to focus their efforts. In this research, we investigate whether variability in the delivery of a health care service is associated with process performance and whether all process variability has equivalent impact on outcomes. We make a distinction between intra-organizational and inter-organizational tasks. Intra-organizational tasks are completed within the boundaries of one organization and are easier to manage, standardize and improve, whereas inter-organizational tasks require two organizations to interact, and are more difficult and complex to manage. Using data collected over a two year period, we examine the effects of intra-organizational and inter-organizational task variability on patient and hospital outcomes. Using in-hospital mortality and length of hospital stay as outcome measures and multivariate statistical analysis, we find that average task activity and its variability's impact on performance differs according to the type of tasks. Our results have implications for both researchers and managers across all professional services. We contribute to theory development for service process design and management by identifying the differing impact of intra-organizational and inter-organizational activities on process outcomes. We also contribute to management practice by providing a means to directly identify targets for improvement.

Dan Snow (HBS)

"Responses to 'Dominant' Technological Threats: Demand Heterogeneity and Graceful Technology Retreats."

Deborah Dougherty (Rutgers)

"Intertwining Therapy Science, Techno Science, and Policy to Enhance (Enable?) Drug Discovery in Bio-Pharma" Abstract: This study unpacks the special, and perhaps very new, challenges of "labyrinthian learning" faced by bio-pharmaceutical drug innovators. We began by examining problems of integrating therapy sciences, techno-sciences, and policy/strategic management around drug development, and find that people in all three are trying to improve drug discovery in conflicting ways. Based on what each knowledge system is trying to accomplish, we identify different problem contexts to be continually set and solved by all three knowledge systems at once, since they mutually constitute the innovation work. All three problem contexts pull together learning from vastly distributed, impersonal networks and also rely on situated, interpersonal knowing: the project, or searching for clues through the living labyrinth; the domain or labyrinth itself, or searching for better ways to search for clues; and the policy/strategy of ambiguity, or searching for better places to search for clues. We propose new ways to use old innovation management ideas to organize these qualitatively new knowledge structures and processes.

Jenny Rudolph (Harvard Medical School), Bradley Morrison (Brandeis University) & John Carroll (MIT)

"The Dynamics of Action-Oriented Problem Solving: Linking Interpretation and Choice" Abstract: We developed a theory of action-oriented problem solving that links interpretation and choice, processes usually separated in the sensemaking and decision making literatures. Through an iterative, simulation-based process we developed a formal model. Three insights emerged: (1) action-oriented problem solving includes acting, interpreting, and cultivating diagnoses; (2) feedback among these processes opens and closes windows of adaptive problem solving; and (3) reinforcing feedback and confirmation bias, usually considered dysfunctional, are helpful for adaptive problem solving.

Brent Goldfarb (University of MD)

"When are there not Bubbles? Investment Patterns in New industries" Abstract: Asset prices will increase when the revealed distribution of risk-reward preferences of investors shifts. We hypothesize that this is more likely to occur in the presence of naive investors. Naivete occurs when either investors are novices or assets are novel to investors. We hypothesize that the two effects are reinforcing and their dual presence is associated with the emergence of bubbles. To test our hypothesis, we survey the history of technology for innovations that might be expected to generate naive enthusiasm among investors, as well as the history of market access. Combining these two analyses offers the possibility to both predict the incidence of bubbles and explain when market bubbles fail to form.

Beril Toktay (GA Tech)

Relicensing as a Secondary Market Strategy Abstract: Secondary markets in the Information Technology (IT) industry, where used or refurbishedequipment is traded, have been growing steadily. For Original Equipment Manufacturers (OEMs)in this industry, the importance of secondary markets has grown in parallel, not only as a sourceof revenue, but also because of their impact on these firms' competitive advantage and marketstrategy. Recent articles in the press have severely criticized some OEMs who are perceived tobe actively trying to eliminate the secondary market for their products. Others have policiesthat enhance their secondary markets. The goal of this paper is to understand how an OEM'sincentives and optimal strategies vis-a-vis the secondary market are shaped contingent on herrelative competitive advantage, product characteristics and consumer preferences. The criticaltradeoff that we examine is whether the indirect benefit from maintaining an active secondarymarket (the resale value effect) can outweigh the potentially negative effect of the sales of usedproducts at the expense of new product sales (the cannibalization effect). To that end, wedevelop a model where the OEM can directly affect the resale value of her product through arelicensing fee charged to the buyer of the refurbished equipment. Moreover, we introduce ameasure of the consumers' willingness to return their used products to account for the fact thatthe higher the price offered by a third-party entrant, the higher the ratio of returned products attheir end-of-use. We analyze the OEM's decision in both the monopoly and the duopoly cases,characterize the optimal relicensing fee set by the OEM, and draw conclusions on the conditionsthat favor stimulating or deterring the secondary market.

Recruiting Seminar

Recruiting Seminar

Recruiting Seminar

Recruiting Seminar

Recruiting Seminar

Recruiting Seminar

Ananth Raman (HBS)

"Understanding and Influencing Operations as an Investor" Abstract: In this talk, I would like to introduce and have a discussion of a new problem area that, I believe, is an interesting and fertile area for further research in operations management. I would like to start by introducing briefly three current research projects. First, I will examine how analysts' sales forecasts can be improved by recognizing the relationship between sales, inventory, and margins. Second, I will examine optimal inventory levels for a newsvendor that is owned by public investors. Third, I will explore the impact of operational "glitches" on a firm's valuation. These three problem areas I hope will serve as a basis for discussing the investor's perspective on operations. This talk will draw substantially on research conducted by Vishal Gaur (Cornell), Saravanan Kesavan (UNC), Richard Lai (Wharton) and Bill Schmidt (Doctoral Student, HBS), and class discussions in an MBA elective with the same title as this talk.

Gary Pisano (HBS) & Roberto Verganti (Politecnico di Milano)

"The Myth of Crowdsourcing."
One of the most important tasks of modern economies is the allocation of human resource talent to problem-solving activities. While economics has explored a broad range of resource allocation problems, precious little is known about the institutional and market mechanisms by which the "right" talent is allocated to the "right" problem. In practice, we see a great deal of experimentation occurring in the organization of problem solving. One trend that has captured the imagination of both scholars and practitioners alike is the increasing use of "open" models of innovation (sometimes referred to as "crowd-sourcing"). As the name implies, open models invite outsiders (individuals, suppliers, customers, even competitors) to participate in the firm's innovation process. By providing access to a broad array of problem-solvers and harnessing market-based incentives, open innovation is presumed to have significant benefits over "closed" approaches. Unfortunately, there has been little comparative analysis of alternative forms of collaboration. Indeed, discussions often equate "open" innovation with "collaborative" innovation. In reality, open models are but one form of the broader phenomenon of collaborative innovation. And, not all forms of collaboration are open. In previous work (G. Pisano and R. Verganti "Which Form of Collaboration is Right for You." Harvard Business Review, December 2008) we provide a typology of alternative forms of collaboration and a framework for comparing the trade-offs inherent in each.

In our current work, and in this workshop, we build on that framework to examine how the choice between "open" and "closed" (elite circle) approaches affects the payoffs to both problem-seekers and problem-solvers. In our model, open innovation involves enticing participants (with a reward), running a competition, and then selecting the best idea. In contrast, "elite circle" models involve selecting the best problem-solver and then committing to pay a fee (regardless of outcome). We introduce two possible sources of market failure in our model. The first is screening costs. To choose the best idea out of many requires some degree of effort (e.g. testing). The same is true for hiring an "elite." There is a cost for finding prospective candidates and deciding if they are worth paying an elite fee. Our model enables us to compare how differential costs of screening people vs. ideas influences the choice of collaborative approach. Second, we allow for the possibility of errors in the selection of both proposed solutions (in the open process) and of prospective elites (for the elite circle). Once we consider these sources of friction, it becomes apparent that open models are likely to outperform closed models only when the cost of screening idea sis low (relative to the costs of screening people) and when the probability of making an error in the selection of an idea is low (relative to the probability of error in selecting people). We discuss the implications of these findings for collaborative innovation and future research.

Karim Lakhani (HBS) and Ned Gulley (The Mathworks)

The Patterns of Innovation Generation in a Collaborative Community: Exploring the relationship between knowledge novelty and reuse
Abstract: We explore the patterns of innovation generation in a collaborative community setting. Community innovation systems are distinguished by their free revealing of knowledge and the ability of actors to reinterpret and repurpose existing knowledge created by others in making their own new creations. We examine if there is consistency amongst the actions of an individual to create effective new innovations and the needs of the many in the community to make use of the efforts of others for their own use. We study this relationship in a unique setting of "wiki-like" collaborative programming contests each involving over a hundred contributors and several thousand attempts at creating the "best" software solution to a difficult programming challenge over a one week period. In particular we investigate; 1)The factors that predict a coding entry being ranked at the top upon submission (top performance) and; 2)The factors that predict increasing using of the new code in an entry by others in the community (social value).

Using data from eleven such contests, involving over 1100 participants and over 26,000 entries, we find that increasing amounts of novel code, both de novo and novel combinations of reused code of others, increases the odds of an individual creating a top performing entry and the subsequent reuse (social value) of the new code by community members. However increasing use of borrowed code (knowledge reuse) in an entry lowers the odds of top performance but increases the social value of the new code indicating a tension between the needs of the individual and the community. Similarly, code structures that are increasingly non-generalizable increase the odds of being a top performer but decrease subsequent reuse by others. Surprisingly, increasing code complexity (non-modularity) raises the odds of top performance and increases social value. We discuss the implications of these findings in light of the literature on collaborative communities of innovation and highlight the importance of considering both individual and community perspectives as it relates to knowledge creation and reuse.

Kristina McElheran (HBS)

"Delegation In Multi-Divisional Firms:Determinants Of The Organizational Structure Of I.T. Purchasing Authority"
This paper investigates how tradeoffs between adaptation and coordination influence the organizational structure of multi-establishment firms - in particular, decision rights over information technology investments. A sizeable economic theory suggests that a strong need for local adaptation will promote decentralized decision making; conversely, demands for intra-firm coordination will encourage centralization. However, data limitations have prevented large-scale empirical validation of these predictions to date. Using a unique data set that links establishment-level use of information technology to the U.S. Census of Manufactures, this paper documents the distribution of IT investment authority across more than 4,000 establishments in a wide range of industries. The data reveal surprising heterogeneity in the locus of authority within a given firm. However, the pattern of this variation is largely consistent with theoretical predictions: site and firm characteristics that increase the value of locally optimal decision making - such as a high contribution to firm revenues or complex or idiosyncratic production- are highly correlated with delegated IT investment authority. Characteristics associated with a high demand for inter-site coordination - such as a high value of intra-firm transfers -are negatively correlated with local discretion. Alternative explanations are found to be less consistent with the observed empirical regularities, subject to the limitations of the data.

Vishal Gaur (Cornell)

"Ordering behavior of retail stores and implications for automated replenishment"
Abstract: Retail store managers may not follow order advices generated by an automated inventory replenishment system if their incentives differ from the cost minimization objective of the system or if they perceive the system to be suboptimal. We study the ordering behavior of retail store managers in a supermarket chain to characterize such deviations in ordering behavior and investigate their potential drivers. Using orders, shipments, and POS data for 19,417 item-store combinations over 5 stores, we find that store managers systematically modify automated order advices by advancing orders from peak to non-peak days. We show that order advancement is explained significantly by hypothesized product characteristics, such as case-pack size relative to average demand per item, net shelf space, product variety, demand uncertainty, and seasonality error. Our results suggest that store managers add value. They improve upon the automated replenishment system by incorporating two ignored factors: in-store handling costs and sales improvement potential through better in-stock. We test a heuristic procedure, based on our regression results, to modify order advices to mimic the behavior of store managers. Our method performs better than the store managers by achieving a more balanced handling workload with similar average days of inventory.

Kathleen Sutcliffe (University of Michigan)

Canceled

Clay Christensen (HBS)

Designing Course Development
Rather than my talking about our most recent research into heath care and public education, a number of TOM faculty have encouraged me instead to continue the discussion I initiated in Kash Rangan's seminar about designing courses. We structured the BSSE course as a vehicle for conducting research even as we teach what we know. If you attended my presentation in Kash's seminar, there is probably no benefit for coming to this one, but I hope you can tolerate an even deeper discussion.

Anita Tucker (HBS)

An Empirical Test of the Impact of Senior Manager Involvement with Front-line Problem-Solving Efforts on Organizational Culture
Abstract: Senior managers influence their organizations' success with process improvement initiatives through their direct actions as well as their role in creating an organizational culture that supports improvement. However, little research examines the mechanisms through with senior manager engagement results in improved outcomes. This study seeks to address these gaps by examining the impact of an 18-month intervention that increased senior managers' engagement in frontline improvement efforts. We distinguish among three specific problem-solving activities-identifying problems, taking action on problems, and providing feedback on actions taken. We selected a random sample of 20 organizations in one industry to participate in our intervention and compared their improvement on organizational climate with 48 non-intervention organizations in the same industry. We found that taking action on a higher percentage of identified problems increased perceptions of organizational climate. Contrary to our expectations, we found that providing feedback about actions taken positively impacted senior managers' perceptions of organizational climate and negatively impacted frontline employees' perceptions. Our results provide empirical evidence that increasing interactions between senior managers and frontline employees will result in improvement only if managers take credible action to resolve the problems that surface through these interactions.

Mike Toffel (HBS)

Operational Failures and Problem Solving
Operational failures occur in all industries, with consequences that range from minor inconveniences to major catastrophes. Many organizations have implemented incident reporting systems to encourage problem solving and support organizational learning in order to prevent future operational failures. Our study is among the first to empirically test theory about which failures are likely to spur such problem solving. We hypothesize that incidents are more salient, and thus more likely to spur problem solving, when they conflict with an organization's mission, involve profitable customer segments, or risk posing legal liability. We further argue that incidents directly involving customers or occurring during periods of low organizational slack are more challenging to address, and are thus less likely to spur problem solving. We test our hypotheses in the health care context using data on 18,000 incidents from a single hospital.

Will Mitchell (Duke)

The hollow corporation revisited: Can governance mechanisms substitute for technical expertise in managing buyer-supplier relationships?
Abstract: This paper considers how a firm's internal technical expertise and its supplier governance mechanisms influence supplier performance, both independently and jointly. The core question is whether inter-firm governance mechanisms, including both contractual and relational mechanisms, can substitute for a firm's internal technical skills in maintaining supplier performance or whether a firm risks hollowing itself out by de-emphasizing internal expertise when it outsources. The arguments build on the capabilities, inter-organizational governance, and supply management literatures. We find that internal technical expertise influences multiple dimensions of supplier performance, including cooperation, price, quality, delivery, and communication, while relational governance has a more focused impact on supplier performance. Combinations of technical expertise, relational governance, and contractual agreements also jointly affect several aspects of supplier performance. Thus, firms generate superior supplier performance if they retain internal technical skills even as they increase their use of external governance mechanisms to manage buyer-supplier relationships.

Robert Klassen (Ivey Business School)

Environmental Management Expenditures: Assessing the Financial Returns from Structural and Infrastructural Investments
Abstract: Management research on green operations has continued to evolve to consider a broad range of management decisions, programs and technologies that contribute to greener operations. After briefly tracing earlier research that explored whether it pays to be green, this presentation uses a multi-dimensional definition of environmental expenditures to examine implications for performance. Multi-year data drawn from several Canadian government databases provided the basis for assessing the financial implications of increased levels and varying allocations of environmental expenditures, and expanding the range of management tools employed. Overall, management practices, including environmental monitoring, assessments, auditing, administering environmental programs, and environmental training, emerged as a key lever in improving manufacturing performance. Both increasing expenditures of and a greater allocation toward management practices yielded positive financial returns across several specific cost and inventory metrics. Finally, I conclude by extending from these results to emerging areas of sustainability-related research in operations management.

Robert Huckman (HBS)

Managing Operational Focus and Growth
Operational focus has been identified as a source of improved productivity based on the premise that "…simplicity, repetition, experience, and homogeneity of tasks breed competence" (Skinner 1974). The repetition underlying focus, however, is challenged when an operation faces the inevitable need to grow. This seminar will present a course module I am developing that brings together cases and research related to the management of this apparent paradox. Our discussion will initially focus on the generic paths by which growth compromises operational focus and will then turn to strategies for managing this tradeoff.

Deishin Lee (HBS)

Leveraging Collateral Output
Accompanying the production of every product in a manufacturing process is a stream of collateral output which is usually ascribed as waste. However, pressure to improve the bottom line and increased scrutiny on environmental impact have driven firms to innovate on ways to manage their waste streams. I characterize an operational model where the input to the process is the collateral output of another process. Using specific examples and analytical models, operational, environmental, and social welfare implications of this operational model are derived.