Search

A questionnaire was developed and administered to the research personnel of "An Foras Taluntais," the Irish agricultural research and development organization, to study the operation of communications channels for the international transfer of technological information. The techniques employed are similar to those used in previous studies of the purely domestic flow of technological information into American research and development laboratories. The international transfer of technology, like domestic transfer, takes place in a two-step process operation through intermediary agents called technological gatekeepers. For greatest effectiveness such technological gatekeepers must be well integrated into two information networks -- an external network of information sources and an internal network of users to whom the information can be delivered. Possible strategies for gatekeeper development are discussed. (Author)

In order to transform the disruptive forces that threaten the university today into cohesive ones, the university should make structural changes within itself toward a new purpose of enhancing society's capability for continuous self-renewal. It may have to become a political institution, interacting with government and industry in the planning and designing of society's systems, and controlling the outcomes of the introduction of technology into these systems. This new leadership role of the university would provide an integrated approach to world systems, particularly the "joint systems" of society and technology. Chapter 1 of the report identifies pressures for change, relates them to causes which are deeply rooted in society, and attempts to redefine the purpose of the university. The structural and operational aspects of an "ideal design" for the new university that would integrate the disruptive forces of change are presented in Chapter 2. Chapter 3 outlines several innovations that may facilitate the transition from the present to the new design of the university. These include pilot system laboratories, interdisciplinary centers for integrative and policy studies, and the introduction of new teaching and research subjects linking scientific and technological issues to others of public policy and social concern. The report is generally based on the present structure of the Massachusetts Institute of Technology. (WM)

Data from a large number of recent research studies are brought to bear on the problem of providing for the technical information needs of research and development projects. The importance of proper support by the technical staff is shown, and it is argued that the best way to couple the project team to information sources outside the organization is by an indirect route through key personnel among the laboratory's technical staff. Informal relations and physical location are shown to be important determinants of the structure of organizational communication networks. Informal relations can be developed through formation of project teams and inter-group transfers and loans. The effect of physical location on communications is especially strong and should be given serious consideration when designing research facilities. (Author)

The purpose of this paper has been to argue the usefulness of path-goal models in theoretical research and practical design of organization reward systems. The reasoning is that the policy choices can be easily related to path-goal attitudes which, in turn, are related to behavior. The major policy choices were identified and related to path-goal attitudes. Finally, some research studies illustrating the use of path-goal models were discussed. (Author)

THE PROCESS OF SUCCESSFUL BEHAVIOR CHANGE IS AFFECTED BY A NUMBER OF SOCIAL AND PSYCHOLOGICAL CHARACTERISTICS OF THE TRANSITIONAL ROLE. SUCCESS IS MEASURED BY A CHANGE IN BEHAVIOR THAT IS SELF-SUSTAINING, LEADING TO SUCCESSFUL OCCUPATION OF A TERMINAL STATUS. ALTHOUGH THE INITIATING OF MEDICAL STUDENTS INTO THE MEDICAL PROFESSION IS GIVEN AS AN EXAMPLE, THE CHARACTERISTICS MENTIONED APPLY IN VARYING DEGREES TO ALL BEHAVIOR CHANGES. A TRANSITIONAL CULTURE RELIEVING THE INDIVIDUAL OF CARES AND RESPONSIBILITIES AND ALLOWING FOR EXPERIMENTATION AND PLAY IS REQUIRED. THE INDIVIDUAL IN SUCCESSFUL TRANSITION EXHIBITS A COMMITMENT TO THE NEW STATUS, AN ARTICULATION OF WHAT THE NEW STATUS IS LIKE, AND A RESERVED JUDGMENT OF HIS ABILITY TO ACHIEVE IT. FURTHERMORE, TOTAL INVOLVEMENT AND THE ACQUISITION OF AN INNER SENSE OF PERSONAL RESPONSIBILITY AND SELF-DIRECTION IS NEEDED. THE EXPECTATIONS OF OTHERS HAVE TO BE ALTERED SO THAT THE INDIVIDUAL IS PERCEIVED AS A LEGITIMATE OCCUPANT OF THE TERMINAL STATUS. FINALLY, INTERPERSONAL RELATIONSHIPS IN THE TRANSITIONAL RULE SHOULD BE DEVELOPED WHICH PROVIDE--(1) THE INTIMACY NECESSARY FOR THE SCANNING AND INTEGRATION OF CHANGES INTO THE PERSONALITY, AND (2) THE INFLUENCE NECESSARY FOR THE TRANSMISSION OF THE INFLUENCING INSTITUTION'S CHANGE GOALS. (CG)

SELF-DESCRIPTIVE ESSAYS WRITTEN BY BUSINESS-SCHOOL STUDENTS WHO WERE SUBSEQUENTLY SUCCESSFUL (N=13) WERE COMPARED WITH THOSE WRITTEN BY STUDENTS UNSUCCESSFUL (N=11) IN ATTAINING PERSONAL CHANGE GOALS DURING SEMESTER-LONG, SELF-ANALYTIC GROUPS. A NEW METHOD FOR SELF-DIRECTED BEHAVIOR CHANGE WAS USED. CONTENT ANALYSIS COMPARISONS OF THE GROUPS REVEALED THREE SIGNIFICANT DIFFERENCES--(1) HIGH-CHANGE SUBJECTS MORE FREQUENTLY STATED GOALS WITH IMPLICIT RECOGNITION THAT THE GOAL HAD NOT YET BEEN ATTAINED, (2) LOW-CHANGE SUBJECTS MORE FREQUENTLY DESCRIBED THEMSELVES WITH LITTLE RECOGNITION OF ALTERNATE POSSIBILITIES, AND (3) LOW-CHANGE SUBJECTS WERE HIGHER IN TENTATIVENESS AND UNCERTAINTY ABOUT THEMSELVES, EXHIBITING IDENTITY DIFFUSION. THESE FINDINGS WERE CROSS-VALIDATED IN A SECOND SAMPLE OF STUDENTS WHO WERE SUCCESSFUL (N=9) AND UNSUCCESSFUL (N=22) IN REACHING THEIR CHANGE GOALS. THE RESULTS SUGGEST THAT SUCCESSFUL SELF-DIRECTED PERSONAL CHANGE IS MOTIVATED BY AWARENESS OF COGNITIVE DISSONANCE CREATED WHEN AN INDIVIDUAL COMMITS HIMSELF TO A VALUED GOAL PERCEIVED AS DIFFERING FROM HIS PRESENT BEHAVIOR. THE LOW-CHANGE SUBJECT IS ONE WHO DOES NOT CREATE COGNITIVE DISSONANCE IN THE PROCESS OF SETTING PERSONAL GOALS EITHER (1) BECAUSE THE GOAL IS IMPERFECTLY DIFFERENTIATED FROM PRESENT BEHAVIOR, OR (2) BECAUSE HE CAN TOLERATE AN UNUSUALLY GREAT AMOUNT OF INTERNAL SELF CONTRADICTION WITHOUT EXPERIENCING DISSONANCE. (AUTHORS/SK)

Last in a series of research projects on the implications of technological change and automation, this study is concerned with the use of computers in formal education and educational administration; in library systems and subsystems; in legal, legislative, and related services; in medical and hospital services; and in national and centralized local data banks. The general implications of computers in all five fields are that: (1) busy specialists and professionals will be relieved of time-consuming, repetitive parts of their work; (2) people in these fields will be provided with computer-based programs in solving problems or advancing their knowledge; (3) computer-based systems may help to reduce shortages of specialists and professional personnel; (4) man-machine interaction systems will spread in these fields; (5) organizations will become more centralized in some of their functions, but decentralized decision making may also be strengthened; and (6) in each of these fields, resistance to changing traditional ways of working and traditional handling of information will continue unless systems designers find ways of explaining what they are trying to do and involving those affected in the design and implementation of computer-based systems. (MF)

This report contains a summary of research done at Alfred P. Sloan School of Management to study the information requirements associated with research and development activity under the headings: parallel projects, laboratory communication networks, characteristic costs of information channels, and interorganizational transfer of information. Principal conclusions and implications of this research are given, and theses, papers and reports produced as part of the research program are listed. Three appendices contain reports on the problem of internal consulting in research and development organizations, information flow in research and development laboratories, and a model for the description and evaluation of technical problem solving. (RP)

The criteria employed by engineers in the selection of various technical information channels in problem-solving endeavors are investigated. The relationships of certain criteria identified in past research to such factors as frequency of channel utilization and the rate at which engineers accept or reject technical information received from specific channels are the focal points of the study. A direct relationship is found between perceived accessibility of information channels and several objective measures of utilization, whereas no definite support is found for the hypothesis that the channels perceived highest in technical quality are those used most frequently. On the other hand, perceived technical quality shows a direct relation to message acceptance ratio. (Author)

Identifying winning new product concepts can be a challenging process that requires insight into private consumer preferences. To measure consumer preferences for new product concepts, the authors apply a “securities trading of concepts,” or STOC, approach, in which new product concepts are traded as financial securities. The authors apply this method because market prices are known to efficiently collect and aggregate private information regarding the economic value of goods, services, and firms, particularly when trading financial securities. This research compares the STOC approach against stated-choice, conjoint, constant-sum, and longitudinal revealed-preference data. The authors also place STOC in the context of previous research on prediction markets and experimental economics. Across multiple product categories, the authors test whether STOC (1) is more cost efficient than other methods, (2) passes validity tests, (3) measures expectations of others, and (4) reveals individual preferences, not just those of the crowd. The results show that traders exhibit a self-preference bias when trading. Ultimately, STOC offers two key advantages over traditional market research methods: cost efficiency and scalability. For new product development teams deciding how to invest resources, this scalability may be especially important in the Web 2.0 world., United States. Office of Naval Research (Contract Number N00014-93-1-3085), National Science Foundation (U.S.). Information Technology Research (Contract Number IIS-0085836), National Science Foundation (U.S.). Knowledge and Distributed Intelligence Initiative (Contract Number DMS-9872936), National Science Foundation (U.S.) (Contract Number IIS-9800032), United States. Office of Naval Research (United States. Defense Advanced Research Projects Agency) (Contract Number N00014-00-1-0907)

We examine a crowdfunding platform that connects artists with funders. Although the Internet reduces many distance-related frictions, local and distant funders exhibit different funding patterns. Local funders appear less responsive to information about the cumulative funds raised by an artist. However, this distance effect appears to proxy for a social effect: it is largely explained by funders who likely have an offline social relationship with the artist (“friends and family”). Yet, this social effect does not persist past the first investment, suggesting that it may be driven by an activity like search but not monitoring. Thus, although the platform seems to diminish many distance-sensitive costs, it does not eliminate all of them. These findings provide a deeper understanding of the abilities and limitations of online markets to facilitate transactions and convey information between buyers and sellers with varying degrees of social connectedness.

Recently proposed ‘megafund’ financing methods for funding translational medicine and drug development require billions of dollars in capital per megafund to de-risk the drug discovery process enough to issue long-term bonds. Here, we demonstrate that the same financing methods can be applied to orphan drug development but, because of the unique nature of orphan diseases and therapeutics (lower development costs, faster FDA approval times, lower failure rates and lower correlation of failures among disease targets) the amount of capital needed to de-risk such portfolios is much lower in this field. Numerical simulations suggest that an orphan disease megafund of only US$575 million can yield double-digit expected rates of return with only 10–20 projects in the portfolio., MIT Laboratory for Financial Engineering

We study support recovery for a $k \times k$ principal submatrix with elevated mean $\lambda/N$, hidden in an $N\times N$ symmetric mean zero Gaussian matrix. Here $\lambda>0$ is a universal constant, and we assume $k = N \rho$ for some constant $\rho \in (0,1)$. We establish that {there exists a constant $C>0$ such that} the MLE recovers a constant proportion of the hidden submatrix if $\lambda {\geq C} \sqrt{\frac{1}{\rho} \log \frac{1}{\rho}}$, {while such recovery is information theoretically impossible if $\lambda = o( \sqrt{\frac{1}{\rho} \log \frac{1}{\rho}} )$}. The MLE is computationally intractable in general, and in fact, for $\rho>0$ sufficiently small, this problem is conjectured to exhibit a \emph{statistical-computational gap}. To provide rigorous evidence for this, we study the likelihood landscape for this problem, and establish that for some $\varepsilon>0$ and $\sqrt{\frac{1}{\rho} \log \frac{1}{\rho} } \ll \lambda \ll \frac{1}{\rho^{1/2 + \varepsilon}}$, the problem exhibits a variant of the \emph{Overlap-Gap-Property (OGP)}. As a direct consequence, we establish that a family of local MCMC based algorithms do not achieve optimal recovery. Finally, we establish that for $\lambda > 1/\rho$, a simple spectral method recovers a constant proportion of the hidden submatrix., Comment: 42 pages, 1 figure

Anecdotes abound suggesting that the use of predictive analytics boosts firm performance. However, large-scale representative data on this phenomenon have been lacking. Working with the Census Bureau, we surveyed over 30,000 American manufacturing establishments on their use of predictive analytics and detailed workplace characteristics. We find that productivity is significantly higher among plants that use predictive analytics—up to $918,000 higher sales compared to similar competitors. Furthermore, both instrumental variables estimates and the timing of gains suggest a causal relationship. However, we find that the productivity pay-off only occurs when predictive analytics are combined with at least one of three workplace complements: significant accumulation of IT capital, educated workers, or workplaces designed for high flow-efficiency production. Our findings support claims that predictive analytics can substantially boost performance, while also explaining why some firms see no benefits at all.

Problem definition : We examine a dynamic assignment problem faced by a large wireless service provider (WSP) that is a Fortune 100 company. This company manages two warranties: (i) a customer warranty that the WSP offers its customers and (ii) an original equipment manufacturer (OEM) warranty that OEMs offer the WSP. The WSP uses devices refurbished by the OEM as replacement devices, and hence their warranty operation is a closed-loop supply chain. Depending on the assignment the WSP uses, the customer and OEM warranties might become misaligned for customer-device pairs, potentially incurring a cost for the WSP. Academic/practical relevance : We identify, model, and analyze a new dynamic assignment problem that emerges in this setting called the warranty matching problem. We introduce a new class of policies, called farsighted policies, which can perform better than myopic policies. We also propose a new heuristic assignment policy, the sampling policy, which leads to a near-optimal assignment. Our model and results are motivated by a real-world problem, and our theory-guided assignment policies can be used in practice; we validate our results using data from our industrial partner. Methodology : We formulate the problem of dynamically assigning devices to customers as a discrete-time stochastic dynamic programming problem. Because this problem suffers from the curse of dimensionality, we propose and analyze a set of reasonable classes of assignment policies. Results : The performance metric that we use for a given assignment policy is the average time that a replacement device under a customer warranty is uncovered by an OEM warranty. We show that our assignment policies reduce the average uncovered time and the expected number of out-of-OEM-warranty returns by more than 75% in comparison with our industrial partner’s current assignment policy. We also provide distribution-free bounds for the performance of a myopic assignment policy and of random assignment, which is a proxy for the WSP’s current policy. Managerial implications : Our results indicate that, in closed-loop supply chains, being completely farsighted might be better than being completely myopic. Also, policies that are effective in balancing short-term and long-term costs can be simple and effective, as illustrated by our sampling policy. We describe how the performance of myopic and farsighted policies depend on the size and length of inventory buildup.

Governing cybersecurity risks from digital trade is a growing responsibility for governments and corporations. This study develops a systematic framework to delineate and analyze the strategies that governments and corporations take to address cybersecurity risks from digital trade. It maps out the current landscape based on a collection of 75 cases where governments and corporations interact to govern transnational cybersecurity risks. This study reveals that: first, governing cybersecurity risks from digital trade is a global issue whereby most governments implement policies with concerning that the cybersecurity risks embedded within purchasing transnational digital products can influence their domestic political and societal systems. Second, governments dominates the governance interactions by implementing trade policies whereas corporations simply comply. Corporations do, however, have chances to take more active roles in constructing the governance system. Third, supply chain cybersecurity risks have more significant impacts on governance mode between governments and corporations whereas concerns on different national cybersecurity risks do not. Fourth, the interactions between governments and corporations reveal the exisitence of loops that can amplify or reduce cybersecurity risks. This provides policy implications on transnational cybersecurity governance for policy makers and business leaders to consider their potential options and understand the global digital trade environment when cybersecurity and digital trade overlap.

Problem Definition:In service operations settings where the difficulty of jobs is unpredictable, workerscan encounter critical incidents (CIs)—jobs which are sufficiently disturbing to challenge workers’ copingmechanisms. We examine the impact of encountering CIs on subsequent operational performance of workers.Academic / Practical Relevance:Prior work has examined the effects of CIs on the long-term psycho-logical health of workers. We demonstrate that encountering CIs has a practically meaningful impact onoperational performance. We also examine the time-dependency and process-dependency of the effect, andanalyze whether it is mitigated by individual characteristics such as age or experience.Methodology:We use data on 902,002 ambulance activations conducted by paramedics at the LondonAmbulance Service (LAS). We define CIs as incidents where patients have a high probability of dying at thescene, and examine the impact of such events on the paramedics’ performance for the remainder of theirshifts. Our outcomes are the completion time of the ambulance activation and each of its five sub-processes.The exogenous assignment of CIs to paramedic crews allows a clean identification of our effect using ashift-level difference-in-differences specification.Results:Crews who have encountered one prior CI (two prior CIs) spend on average 2.6% (7.5%) moretime completing each remaining ambulance activation in the shift. The impact is strongest for the jobsimmediately following a CI but persists throughout the shift. The largest effects come from the sub-processeswhich are least standardized and where paramedics cannot rely on standard operating procedures. Theduration effect is larger for teams of older paramedics, but is simultaneously mitigated by experience.Managerial Implications:Our results show that CIs increase subsequent job duration and that more thanone CIs have a compounding, negative effect on operational performance. As a result, managers in settingswhere performance consistency is key would be advised not to assign new jobs to teams with recent CI experiences.

Promotions are a critical decision for supermarket managers, who must decide the price promotions for a large number of items. Retailers often use promotions to boost the sales of the different items by leveraging the cross-item effects. We formulate the promotion optimization problem for multiple items as a nonlinear integer program. Our formulation includes several business rules as constraints. Our demand models can be estimated from data and capture the postpromotion dip effect and cross-item effects (substitution and complementarity). Because demand functions are typically nonlinear, the exact formulation is intractable. To address this issue, we propose a general class of integer programming approximations. For demand models with additive cross-item effects, we prove that it is sufficient to account for unilateral and pairwise contributions and derive parametric bounds on the performance of the approximation. We also show that the unconstrained problem can be solved efficiently via a linear program when items are substitutable and the price set has two values. For more general cases, we develop efficient rounding schemes to obtain an integer solution. We conclude by testing our method on realistic instances and convey the potential practical impact for retailers., National Science Foundation (U.S.) (Grant CMMI-1162034)

Most online content publishers have moved to subscription-based business models regulated by digital paywalls. But the managerial implications of such freemium content offerings are not well understood. We, therefore, utilized microlevel user activity data from the New York Times to conduct a large-scale study of the implications of digital paywall design for publishers. Specifically, we use a quasi-experiment that varied the (1) quantity (the number of free articles) and (2) exclusivity (the number of available sections) of free content available through the paywall to investigate the effects of paywall design on content demand, subscriptions, and total revenue. The paywall policy changes we studied suppressed total content demand by about 9.9%, reducing total advertising revenue. However, this decrease was more than offset by increased subscription revenue as the policy change led to a 31% increase in total subscriptions during our seven-month study, yielding net positive revenues of over $230,000. The results confirm an economically significant impact of the newspaper’s paywall design on content demand, subscriptions, and net revenue. Our findings can help structure the scientific discussion about digital paywall design and help managers optimize digital paywalls to maximize readership, revenue, and profit. This paper was accepted by Chris Forman, information systems.

International audience

We provide a survey of 31 quantitative measures of systemic risk in the economics and finance literature, chosen to span key themes and issues in systemic risk measurement and management. We motivate these measures from the supervisory, research, and data perspectives in the main text and present concise definitions of each risk measure—including required inputs, expected outputs, and data requirements—in an extensive Supplemental Appendix. To encourage experimentation and innovation among as broad an audience as possible, we have developed an open-source Matlab® library for most of the analytics surveyed, which, once tested, will be accessible through the Office of Financial Research (OFR) at http://www.treasury.gov/initiatives/wsr/ofr/Pages/default.aspx., United States. Dept. of the Treasury. Office of Financial Research, Massachusetts Institute of Technology. Laboratory for Financial Engineering, National Science Foundation (U.S.) (Grant ECCS-1027905)

We establish a link between illiquidity and positive autocorrelation in asset returns among a sample of hedge funds, mutual funds, and various equity portfolios. For hedge funds, this link can be confirmed by comparing the return autocorrelations of funds with shorter vs. longer redemption-notice periods. We also document significant positive return-autocorrelation in portfolios of securities that are generally considered less liquid, e.g., small-cap stocks, corporate bonds, mortgage-backed securities, and emerging-market investments. Using a sample of 2,927 hedge funds, 15,654 mutual funds, and 100 size- and book-to-market-sorted portfolios of US common stocks, we construct autocorrelation-sorted long/short portfolios and conclude that illiquidity premia are generally positive and significant, ranging from 2.74% to 9.91% per year among the various hedge funds and fixed-income mutual funds. We do not find evidence for this premium among equity and asset-allocation mutual funds, or among the 100 US equity portfolios. The time variation in our aggregated illiquidity premium shows that while 1998 was a difficult year for most funds with large illiquidity exposure, the following four years yielded significantly higher illiquidity premia that led to greater competition in credit markets, contributing to much lower illiquidity premia in the years leading up to the Financial Crisis of 2007–2008.

© International Association for Cryptologic Research 2017. We show a general compiler that transforms a large class of erroneous cryptographic schemes (such as public-key encryption, indistinguishability obfuscation, and secure multiparty computation schemes) into perfectly correct ones. The transformation works for schemes that are correct on all inputs with probability noticeably larger than half, and are secure under parallel repetition. We assume the existence of one-way functions and of functions with deterministic (uniform) time complexity 2O(n) and non-deterministic circuit complexity 2Ω(n). Our transformation complements previous results that showed how public-key encryption and indistinguishability obfuscation that err on a noticeable fraction of inputs can be turned into ones that for all inputs are often correct. The technique relies on the idea of “reverse randomization” (Naor, Crypto 1989) and on Nisan-Wigderson style derandomization, previously used in cryptography to remove interaction from witnessindistinguishable proofs and commitment schemes (Barak, Ong and Vadhan, Crypto 2003)., NSF (Grants CNS-1350619 and CNS-1414119)

doi: 10.1177/26317877221098766 Organization scholars have increasingly looked to the multinational corporation (MNC) as a convenient research site for testing and developing general hypotheses applicable to any organization. In this essay, we argue that theorizing about organizational processes in the MNC needs to treat the MNC itself as a research object: that is, to recognize that the complex multidimensionality of the MNC will influence the phenomena under investigation and needs to be incorporated into research design and conceptual framing. To do so requires what we term contextualized explanations: styles of theorizing that view context as constitutive of organizational phenomena. We reanalyse an existing study of identity work in the Carlsberg Group to demonstrate the theoretical insights to be gained from a contextualized approach. Our case analysis illustrates how integrating the MNC into the explanation changes our theoretical understanding of the phenomena being investigated.

We apply machine-learning techniques to construct nonlinear nonparametric forecasting models of consumer credit risk. By combining customer transactions and credit bureau data from January 2005 to April 2009 for a sample of a major commercial bank’s customers, we are able to construct out-of-sample forecasts that significantly improve the classification rates of credit-card-holder delinquencies and defaults, with linear regression R2’s of forecasted/realized delinquencies of 85%. Using conservative assumptions for the costs and benefits of cutting credit lines based on machine-learning forecasts, we estimate the cost savings to range from 6% to 25% of total losses. Moreover, the time-series patterns of estimated delinquency rates from this model over the course of the recent financial crisis suggest that aggregated consumer credit-risk analytics may have important applications in forecasting systemic risk., Massachusetts Institute of Technology. Laboratory for Financial Engineering, Massachusetts Institute of Technology. Center for Future Banking

In services where teams come together for short collaborations, managers are often advised to strive for high team familiarity so as to improve coordination and consequently, performance. However, inducing high team familiarity by keeping team membership intact can limit workers’ opportunities to acquire useful knowledge and alternative practices from exposure to a broader set of partners. We introduce an empirical measure for prior partner exposure and estimate its impact (along with that of team familiarity) on operational performance using data from the London Ambulance Service. Our analysis focuses on ambulance transports involving new paramedic recruits, where exogenous changes in team membership enable identification of the performance effect. Specifically, we investigate the impact of prior partner exposure on time spent during patient pickup at the scene and patient handover at the hospital. We find that the effect varies with the process characteristics. For the patient pickup process, which is less standardized, greater partner exposure directly improves performance. For the more standardized patient handover process, this beneficial effect is triggered beyond a threshold of sufficient individual experience. In addition, we find some evidence that this beneficial performance impact of prior partner exposure is amplified during periods of high workload, particularly for the patient handover process. Finally, a counterfactual analysis based on our estimates shows that a team formation strategy emphasizing partner exposure outperforms one that emphasizes team familiarity by about 9.2% in our empirical context., Deloitte Institute of Innovation and Entrepreneurship

Effective responses to the COVID‐19 pandemic require integrating behavioral factors such as risk‐driven contact reduction, improved treatment, and adherence fatigue with asymptomatic transmission, disease acuity, and hospital capacity. We build one such model and estimate it for all 92 nations with reliable testing data. Cumulative cases and deaths through 22 December 2020 are estimated to be 7.03 and 1.44 times official reports, yielding an infection fatality rate (IFR) of 0.51 percent, which has been declining over time. Absent adherence fatigue, cumulative cases would have been 47 percent lower. Scenarios through June 2021 show that modest improvement in responsiveness could reduce cases and deaths by about 14 percent, more than the impact of vaccinating half of the population by that date. Variations in responsiveness to risk explain two orders of magnitude difference in per‐capita deaths despite reproduction numbers fluctuating around one across nations. A public online simulator facilitates scenario analysis over the coming months. © 2021 System Dynamics Society.

The confluence of three trends in the U.S. residential housing market---rising home prices, declining interest rates, and near-frictionless refinancing opportunities---led to vastly increased systemic risk in the financial system. Individually, each of these trends is benign, but when they occur simultaneously, as they did over the past decade, they impose an unintentional synchronization of homeowner leverage. This synchronization, coupled with the indivisibility of residential real estate that prevents homeowners from deleveraging when property values decline and homeowner equity deteriorates, conspire to create a "ratchet" effect in which homeowner leverage is maintained or increased during good times without the ability to decrease leverage during bad times. If refinancing-facilitated homeowner-equity extraction is sufficiently widespread---as it was during the years leading up to the peak of the U.S. residential real-estate market---the inadvertent coordination of leverage during a market rise implies higher correlation of defaults during a market drop. To measure the systemic impact of this ratchet effect, we simulate the U.S. housing market with and without equity extractions, and estimate the losses absorbed by mortgage lenders by valuing the embedded put-option in non-recourse mortgages. Our simulations generate loss estimates of $1.5 trillion from June 2006 to December 2008 under historical market conditions, compared to simulated losses of $280 billion in the absence of equity extractions.

Shared appreciation mortgages (SAMs) feature mortgage payments that adjust with house prices. They are designed to stave off borrower default by providing payment relief when house prices fall. Some argue that SAMs may help prevent the next foreclosure crisis. However, home owners' gains from payment relief are mortgage lenders' losses. A general equilibrium model in which financial intermediaries channel savings from saver to borrower households shows that indexation of mortgage payments to aggregate house prices increases financial fragility, reduces risk‐sharing, and leads to expensive financial sector bailouts. In contrast, indexation to local house prices reduces financial fragility and improves risk‐sharing.

Omnichannel marketing is often viewed as the panacea for one-to-one marketing, but this strategic path is mired with obstacles. This article investigates three challenges in realizing the full potential of omnichannel marketing: (1) data access and integration, (2) marketing attribution, and (3) consumer privacy protection. While these challenges predate omnichannel marketing, they are exacerbated in a digital omnichannel environment. This article argues that advances in machine learning and blockchain offer some promising solutions. In turn, these technologies present new challenges and opportunities for firms, which warrant further academic research. The authors identify both recent developments in practice and promising avenues for future research. Editor’s Note: This article is part of the JM-MSI Special Issue on “From Marketing Priorities to Research Agendas,” edited by John A. Deighton, Carl F. Mela, and Christine Moorman. Written by teams led by members of the inaugural class of MSI Scholars, these articles review the literature on an important marketing topic reflected in the MSI Priorities and offer an expansive research agenda for the marketing discipline. A list of articles appearing in the Special Issue can be found at http://www.ama.org/JM-MSI-2020.

Problem definition: We examine how a profit-driven firm (she) can motivate better social responsibility (SR) practices by a supplier (he) when these practices cannot be perfectly observed by the firm. We focus on the firm’s investment in the supplier’s SR capabilities. To capture the influence of consumer demands, we incorporate the potential for SR information to be disclosed by the firm or revealed by a third party. Academic/practical relevance: Most firms have limited visibility into the SR practices of their suppliers. However, there is little research on how a firm under incomplete visibility should (i) invest to improve a supplier’s SR practices and (ii) disclose SR information to consumers. We address this gap. Methodology: We develop a game-theoretic model with asymmetric information to study a supply chain with one supplier and one firm. The firm makes her investment decision given incomplete information about the supplier’s current SR practices. We analyze and compare two settings: the firm does not disclose versus she discloses SR information to the consumers. Results: The firm should invest a high (low) amount in the supplier’s capabilities if the information she observes suggests the supplier’s current SR practices are poor (good). She should always be more aggressive with her investment when disclosing (versus not disclosing). This more aggressive strategy ensures better supplier SR practices under disclosure. When choosing between disclosing and not disclosing, the firm most likely prefers not to disclose when the supplier’s current SR practices seem to be average. Managerial implications: (i) Greater visibility helps the firm to better tailor her investment to the level of support needed. (ii) Better visibility also makes the firm more “truthful” in her disclosure, whereas increased third-party scrutiny makes her more “cautious.” (iii) Mandating disclosure is most beneficial for SR when the suppliers’ current practices seem to be average.

We develop a theory that shows signaling a firm’s fundamental quality (e.g., its operational capabilities) to lenders through inventory transactions to be more efficient—it leads to less costly operational distortions—than signaling through loan requests, and we characterize how the efficiency gains depend on firm operational characteristics, such as operating costs, market size, and inventory salvage value. Signaling through inventory being only tenable when inventory transactions are verifiable at low enough cost, we then turn our attention to how this verifiability can be achieved in practice and argue that blockchain technology could enable it more efficiently than traditional monitoring mechanisms. To demonstrate, we develop b_verify, an open-source blockchain protocol that leverages Bitcoin to provide supply chain transparency at scale and in a cost-effective way. The paper identifies an important benefit of blockchain adoption—by opening a window of transparency into a firm’s supply chain, blockchain technology furnishes the ability to secure favorable financing terms at lower signaling costs. Furthermore, the analysis of the preferred signaling mode sheds light on what types of firms or supply chains would stand to benefit the most from this use of blockchain technology. This paper was accepted by Victor Martínez-de-Albéniz, operations management.

We study how small and medium enterprise (SME) lenders react to information about their competitors’ contracting decisions. To isolate this learning from lenders’ common reactions to unobserved shocks to fundamentals, we exploit the staggered entry of lenders into an information-sharing platform. Upon entering, lenders adjust their contract terms toward what others offer. This reaction is mediated by the distribution of market shares: lenders with higher shares or that operate in concentrated markets react less. Thus, contract terms are shaped not only by borrower or lender fundamentals but also by the interaction between information availability and competition.

The Dodd-Frank Act mandates that certain standard over-the-counter (OTC) derivatives must be traded on swap execution facilities (SEFs). Using message-level data, we provide a granular analysis of dealers’ and customers’ trading behavior on the two largest dealer-to-customer SEFs for index credit default swaps (CDS). On average, a typical customer contacts few dealers when seeking liquidity. A theoretical model shows that the benefit of competition through wider order exposure is mitigated by a winner’s curse problem and dealer-customer relationships. Consistent with the model, we find that order size, market conditions, and customer-dealer relationships are important empirical determinants of customers’ choice of trading mechanism and dealers’ liquidity provision.

Digitization makes it easier for firms to build their innovation and marketing efforts around consumers' personal data. In this research, we employ a privacy perspective based on contextual integrity to examine how such practices can trigger privacy concerns. We propose that small entrepreneurial firms are often at a particular disadvantage compared to large incumbent firms. At the same time, we also highlight that there are several strategies firms can use to mitigate privacy concerns and that in some circumstances, privacy concerns may also exert positive effects on data-driven marketing by stimulating privacy innovation and providing a source of competitive advantage.

The new coronavirus disease 2019 (COVID-19) has required the implementation of severe mobility restrictions and social distancing measures worldwide. While these measures have been proven effective in abating the epidemic in several countries, it is important to estimate the effectiveness of testing and tracing strategies to avoid a potential second wave of the COVID-19 epidemic. We integrate highly detailed (anonymized, privacy-enhanced) mobility data from mobile devices, with census and demographic data to build a detailed agent-based model to describe the transmission dynamics of SARS-CoV-2 in the Boston metropolitan area. We find that enforcing strict social distancing followed by a policy based on a robust level of testing, contact-tracing and household quarantine, could keep the disease at a level that does not exceed the capacity of the health care system. Assuming the identification of 50% of the symptomatic infections, and the tracing of 40% of their contacts and households, which corresponds to about 9% of individuals quarantined, the ensuing reduction in transmission allows the reopening of economic activities while attaining a manageable impact on the health care system. Our results show that a response system based on enhanced testing and contact tracing can play a major role in relaxing social distancing interventions in the absence of herd immunity against SARS-CoV-2.

Many products have similar or common attributes and are thus correlated. We show that, when these attributes are uncertain for consumers, a complementarity effect can arise among competing products in the sense that the lower price of one product may increase the demands for the others. This effect occurs when consumers sequentially search for information about both common and idiosyncratic product attributes before purchase. We characterize the optimal search strategy for the correlated search problem, provide the conditions for the existence of the complementarity effect, and show that the effect is robust under a wide range of alternative assumptions. We further explore the implications of the effect for pricing. When firms compete in price, although product correlation may weaken differentiation between the firms, the complementarity effect owing to correlated search may raise equilibrium price and profit. This paper was accepted by Matthew Shum, marketing.

We use the staggered introduction of a major financial-reporting regulation worldwide to study whether firms make financing decisions consistent with the pecking order theory. Exploiting cross-country and within country-year variation, we document that treated firms increase their issuance of external financing (and ultimately increase investment) after the new regime. Furthermore, firms make different leverage decisions (debt vs equity) around the new regulation depending on their ex-ante debt capacity, which allows them to adjust their capital structure. Our findings highlight the importance of the pecking order theory in explaining financing as well as investment policies.

Using a 20-month qualitative study of four US states that implemented career pathways spanning from high schools to colleges to employers, the authors illustrate the potential for state government actors to facilitate coordination of workforce development systems across geographies and industries. As a complement to explanations situated in workforce intermediary practices or formal state policies, the authors show that state actors can address barriers to coordination by using state actor orchestration—structuring provisional goal setting and revision, encouraging experimentation, and framing coordination to inspire collective action. This approach involves three types of practices: structural (building statewide governance structures and modifying governance processes), political (providing initial direction and piloting and broadening the set of stakeholders), and cultural (identifying key problems and collective action solutions and building social accountability for new roles). These practices vary according to states’ institutional environments: Where governance is more centralized, state actors gain latitude to guide regional workforce development.

Kenneth Gillingham is an Associate Professor of Economics at Yale University, with a primary appointment in the School of Forestry & Environmental Studies. In 2015 to 2016, he served as the Senior Economist for Energy and the Environment at the White House Council of Economic Advisers. His research interests cover energy and environmental economics, industrial organization, technological change, and energy modeling. He held a Fulbright to New Zealand and has worked for Resources for the Future and Pacific Northwest National Laboratory. He received a PhD and two MS degrees from Stanford University and an AB from Dartmouth College. Christopher Knittel is the George P. Shultz Professor of Applied Economics in the Sloan School of Management at the Massachusetts Institute of Technology (MIT). He is also the Director of MIT’s Center for Energy and Environmental Policy Research, which serves as the hub for social science research on energy and the environmental since the late 1970s. Professor Knittel is also the Co-Director of the MIT Energy Initiative’s Electric Power System Low Carbon Energy Center and a co-director of The E2e Project, a research initiative between MIT, UC Berkeley, and the University of Chicago to undertake rigorous evaluation of energy efficiency investments. Jing Li holds the inaugural William Barton Rogers Career Development Chair of Energy Economics at the MIT Sloan School of Management. From 2017–2018, Jing Li was a Postdoctoral Associate of the MIT Energy Initiative. Jing’s research interests lie in energy economics and industrial organization, focusing on development and adoption of new technologies. Her most recent work examines compatibility and investment in electric vehicle recharging networks in the United States and cost pass-through in the E85 retail market. Jing received double BSc degrees in Mathematics and Economics from MIT in 2011 and her PhD in Economics from Harvard in 2017. Marten Ovaere is a Postdoctoral Associate in the School of Forestry & Environmental Studies of Yale University. His research interests lie in energy and environmental economics, with a focus on electricity markets, carbon pricing, and renewable energy. Marten holds a MSc in Economics, a MSc in Energy Engineering, and a PhD in Economics from KU Leuven. Mar Reguant is an Associate Professor in Economics at Northwestern University. She received her PhD from MIT in 2011. Her research uses high-frequency data to study the impact of auction design and environmental regulation on electricity markets and energy-intensive industries. She has numerous awards, including a Sloan Research Fellowship in 2016, the Sabadell Prize for Economic Research in 2017, a Presidential Early Career Award for Scientists and Engineers award in 2019, and the European Association of Environmental and Resource Economists Award for Researchers in Environmental Economics under the Age of Forty in 2019., The short-run effects of Covid-19 in reducing CO2 and local air pollutant emissions can easily be outweighed by the long-run effects on innovation. In the short-run, CO2 emissions have declined by 15%, and declines in local air pollutants have saved 200 lives per month. However, there could be a deep impact on innovation in clean energy, leading to an additional 2,500 MMT CO2 cumulatively and 40 deaths per month on average to 2035. But the policy response to Covid-19 is crucial.

Understanding the state of the COVID‐19 pandemic relies on infection and mortality data. Yet official data may underestimate the actual cases due to limited symptoms and testing capacity. We offer a simulation‐based approach which combines various sources of data to estimate the magnitude of outbreak. Early in the epidemic we applied the method to Iran's case, an epicenter of the pandemic in winter 2020. Estimates using data up to March 20th, 2020, point to 916,000 (90% UI: 508 K, 1.5 M) cumulative cases and 15,485 (90% UI: 8.4 K, 25.8 K) total deaths, numbers an order of magnitude higher than official statistics. Our projections suggest that absent strong sustaining of contact reductions the epidemic may resurface. We also use data and studies from the succeeding months to reflect on the quality of original estimates. Our proposed approach can be used for similar cases elsewhere to provide a more accurate, early, estimate of outbreak state. © 2020 System Dynamics Society

Blockchain technology can shape innovation and competition in digital platforms, but under what conditions?