Buyers often make supplier selection decisions under conditions of uncertainty. Although the analytical aspects of supplier selection are well developed, the psychological aspects are less so. This article uses supply chain management and behavioral decision theories to propose that attributes of the purchasing situation (category difficulty, category importance, and contingent pay) affect cognition that, in turn, affects a supply manager's choice. We conducted a supplier selection behavioral experiment with practicing managers to test the model's hypotheses. When the context involves an important or difficult sourcing category, higher risk perceptions exist that increase preference for a supplier with more certain outcomes, even when that choice has a lower expected payoff. However, the presence of contingent pay decreases risk perceptions through higher perceived supplier control. We also find that a manager's risk propensity increases preferences for a supplier with less certain outcomes regardless of perceived risk. Our model and results provide a theoretical framework for further study into the cognitive aspects of supplier selection behavior and provide insight into biases that influence practicing supply chain managers.

We report the results of an ethnographic study of a natural food cooperative in which we found an inherent tension in its mission between idealism and pragmatism, and we explore the dynamics through which that tension was managed and engaged in day-to-day governance and activities. Insights from participant observation, archival data, semi-structured interviews, and surveys provide a detailed and holistic account of the intergroup and intragroup processes through which the co-op negotiated its dualistic nature, as embodied in its hybrid organizational identity. The findings suggest that the value of each side of the duality was recognized at both the individual and organizational levels. Members’ discomfort with the duality, however, led them to split the mission in two and identify with one part, while projecting their less-favored part on others, creating an identity foil (an antithesis). This splitting resulted in ingroups and outgroups and heated intergroup conflict over realizing cooperative ideals vs. running a viable business. Ingroup members favoring one part of the mission nonetheless identified with the outgroup favoring the other because it embodied a side of themselves they continued to value. Individuals who exemplified their ingroup’s most extreme attributes were seen by the outgroup as prototypical, thus serving as “lightning rods” for intergroup conflict; this dynamic paradoxically enabled other ingroup members to work more effectively with moderate members of the outgroup. The idealist–pragmatist duality was kept continually in play over time through oscillating decisions and actions that shifted power from one group to the other, coupled with ongoing rituals to repair and maintain relationships disrupted by the messiness of the process. Thus ostensible dysfunctionality at the group level fostered functionality at the organizational level.

Consumers often face situations in which their feelings of personal control are threatened. In such contexts, what role should products play in helping consumers pursue their goals (e.g., losing weight, maintaining a clean home)? Across five studies, we challenge the traditional view that low control is detrimental to effort and demonstrate that consumers prefer products that require them to engage in hard work when feelings of control are low. Such high-effort products reassure individuals that desired outcomes are possible while also enabling them to feel as if they have driven their own outcomes. We also identify important boundary conditions, finding that both the nature of individuals' thoughts about control and their perceived rate of progress toward goals are important factors in the desire to exert increased effort.

The current research examines how the price of a medication influences consumers’ beliefs about their own disease risk—a critical question with new laws mandating greater price transparency for health care goods and services. Four studies reveal that consumers believe that lifesaving health goods are priced according to perceived need (i.e., communal-sharing principles) and that price consequently influences risk perceptions and intentions to consume care. Specifically, consumers believe that lower medication prices signal greater accessibility to anyone in need, and such accessibility thus makes them feel that their own self-risk is elevated, increasing consumption. The reverse is true for higher prices. Importantly, these effects are limited to self-relevant health threats and reveal that consumers make inconsistent assumptions about risk, prevalence, and need with price exposure. These findings suggest that while greater price transparency may indeed reduce consumption of higher-priced goods, it may do so for both necessary and unnecessary care.

Collaborating with a supplier in a buying firm's new product development (NPD) project is commonly advocated and adopted, but does not always improve project performance. Some pre-existing collaboration contexts, such as buyer–supplier NPD projects, are especially exposed to supplier opportunism due to the uncertain nature of the collaboration process. Adopting agency theory and transaction cost theory perspectives, we examine: (i) contextual antecedents and project consequences of supplier opportunism and (ii) if these causal influences vary in different cultural and institutional contexts. Using a survey sample of 214 United States (U.S.) and 212 Chinese buying firms’ responses about buyer–supplier NPD projects, we find that supplier opportunism is significantly influenced by the task and relational contexts. We also show that supplier opportunism damages both design quality and efficiency, two aspects of project performance. When comparing U.S. to China, we find that task and relational contexts have a greater impact on supplier opportunism in the U.S., but design efficiency is less hurt by supplier opportunism there. Finally, we show challenges of preventing supplier opportunism in certain NPD collaboration contexts, and offer solutions for overcoming these challenges.

Operations managers clearly play a critical role in targeting plant-level investments toward environment and safety practices. In principle, a “rational” response would be to align this investment with senior management's competitive goals for operational performance. However, operations managers also are influenced by contingent factors, such as their national culture, thus creating potential tension that might bias investment away from a simple rational response. Using data from 1,453 plants in 24 countries, we test the moderating influence of seven of the national cultural characteristics on investment at the plant level in environment and safety practices. Four of the seven national cultural characteristics from GLOBE (i.e., uncertainty avoidance, in-group collectivism, future orientation and performance orientation) shifted investment away from an expected “rational” response. Positive bias was evident when the national culture favored consistency and formalized procedures and rewarded performance improvement. In contrast, managers exhibited negative bias when familial groups and local coalitions were powerful, or future outcomes—rather than current actions—were more important. Overall, this study highlights the critical importance of moving beyond a naïve expectation that plant-level investment will naturally align with corporate competitive goals for environment and safety. Instead, the national culture where the plant is located will influence these investments, and must be taken into account by senior management.

We examine the relation between high frequency quotation and the behavior of stock prices between 2009 and 2011 for the full cross section of securities in the US. On average, higher quotation activity is associated with price series that more closely resemble a random walk, and significantly lower cost of trading. We also explore market resiliency during periods of exceptionally high low-latency trading: large liquidity drawdowns in which, within the same millisecond, trading algorithms systematically sweep large volume across multiple trading venues. Although such large drawdowns incur trading costs, they do not appear to degrade the price formation process or increase the subsequent cost of trading. In an out-of-sample analysis, we investigate an exogenous technological change to the trading environment on the Tokyo Stock Exchange that dramatically reduces latency and allows co-location of servers. This shock also results in prices more closely resembling a random walk and a sharp decline in the cost of trading.

This article develops welfare-consistent measures of the employment effects of environmental regulation. Our analysis is based on a microeconomic model of how households with heterogeneous preferences and skills decide where to live and work. We use the model to examine how job loss and unemployment would affect workers in Northern California. Our stylized simulations produce earnings losses that are consistent with empirical evidence. They also produce two new insights. First, we find that earnings losses are sensitive to business cycle conditions. Second, we find that earnings losses may substantially understate welfare losses once we account for the fact that workers may have to commute further or live in a less desirable community after losing a job.

With the advent of high-dimensional stored big data and streaming data, suddenly machine learning on a very large scale has become a critical need. Such machine learning should be extremely fast, should scale up easily with volume and dimension, should be able to learn from streaming data, should automatically perform dimension reduction for high-dimensional data, and should be deployable on hardware. Neural networks are well positioned to address these challenges of large scale machine learning. In this paper, we present a method that can effectively handle large scale, high-dimensional data. It is an online method that can be used for both streaming and large volumes of stored big data. It primarily uses Kohonen nets, although only a few selected neurons (nodes) from multiple Kohonen nets are actually retained in the end; we discard all Kohonen nets after training. We use Kohonen nets both for dimensionality reduction through feature selection and for building an ensemble of classifiers using single Kohonen neurons. The method is meant to exploit massive parallelism and should be easily deployable on hardware that implements Kohonen nets. Some initial computational results are presented.

Based on considerable neurophysiological evidence, Roy (2012) proposed the theory that localist representation is widely used in the brain, starting from the lowest levels of processing. Grandmother cells are a special case of localist representation. In this article, I present the theory that grandmother cells are also widely used in the brain. To support the proposed theory, I present neurophysiological evidence and an analysis of the concept of grandmother cells. Konorski (1967) first predicted the existence of grandmother cells (he called them “gnostic” neurons) - single neurons that respond to complex stimuli such as faces, hands, expressions, objects, and so on. The term “grandmother cell” was introduced by Jerry Lettvin in 1969 (Barlow, 1995).