This article outlines the mechanism by which brokerage provides social capital. Opinion and behavior are more homogeneous within than between groups, so people connected across groups are more familiar with alternative ways of thinking and behaving. Brokerage across the structural holes between groups provides a vision of options otherwise unseen, which is the mechanism by which brokerage becomes social capital. I review evidence consistent with the hypothesis, then look at the networks around managers in a large American electronics company. The organization is rife with structural holes, and brokerage has its expected correlates. Compensation, positive performance evaluations, promotions, and good ideas are disproportionately in the hands of people whose networks span structural holes. The between-group brokers are more likely to express ideas, less likely to have ideas dismissed, and more likely to have ideas evaluated as valuable. I close with implications for creativity and structural change.

https://www.jstor.org/stable/pdf/10.1086/421787.pdf

Structural Holes and Good Ideas.

http://onemvweb.com/sources/sources/network_structure_social_capital.pdf

The Network Structure Of Social Capital

A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

/pdf/metaheuristics-from-design-to-implementation-1vqdfv8nk9.pdf

Metaheuristics: From Design to Implementation

Leveraging the recent research interest in emerging economies, this Perspective paper argues that an institution-based view of international business (IB) strategy has emerged. It is positioned as one leg that helps sustain the “strategy tripod” (the other two legs consisting of the industry- and resource-based views). We then review four diverse areas of substantive research: (1) antidumping as entry barriers; (2) competing in and out of India; (3) growing the firm in China; and (4) governing the corporation in emerging economies. Overall, we argue that an institution-based view of IB strategy, in combination with industry- and resource-based views, will not only help sustain a strategy tripod, but also shed significant light on the most fundamental questions confronting IB, such as “What drives firm strategy and performance in IB?”

/pdf/an-institution-based-view-of-international-business-strategy-b2jah8hc81.pdf

An institution-based view of international business strategy: a focus on emerging economies

What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Quantity-Based RM.- Single-Resource Capacity Control.- Network Capacity Control.- Overbooking.- Price-based RM.- Dynamic Pricing.- Auctions.- Common Elements.- Customer-Behavior and Market-Response Models.- The Economics of RM.- Estimation and Forecasting.- Industry Profiles.- Implementation.

/pdf/the-theory-and-practice-of-revenue-management-3ziygkdk8b.pdf

The Theory and Practice of Revenue Management

Customer choice behavior, such as buy-up and buy-down, is an important phenomenon in a wide range of revenue management contexts. Yet most revenue management methodologies ignore this phenomenon - or at best approximate it in a heuristic way. In this paper, we provide an exact and quite general analysis of this problem. Specifically, we analyze a single-leg reserve management problem in which the buyers' choice behavior is modeled explicitly. The choice model is very general, simply specifying the probability of purchase for each fare product as a function of the set of fare products offered. The control problem is to decide which subset of fare products to offer at each point in time. We show that the optimal policy for this problem has a quite simple form. Namely, it consists of identifying an ordered family of "efficient" subsets S 1 ,..., S m , and at each point in time opening one of these sets S k , where the optimal index k is increasing in the remaining capacity x and decreasing in the remaining time. That is, the more capacity (or less time) available, the further the optimal set is along this sequence. We also show that the optimal policy is a nested allocation policy if and only if the sequence of efficient sets is nested, that is S 1 ? S 2 ?... ? S m . Moreover, we give a characterization of when nesting by fare order is optimal. We also develop an estimation procedure for this setting based on the expectation-maximization (EM) method that jointly estimates arrival rates and choice model parameters when no-purchase outcomes are unobservable. Numerical results are given to illustrate both the model and estimation procedure.

/pdf/revenue-management-under-a-general-discrete-choice-model-of-2vdsjyi74w.pdf

Revenue Management Under a General Discrete Choice Model of Consumer Behavior

Bid-prices are becoming an increasingly popular method for controlling the sale of inventoryin revenue management applications. In this form of control, threshold-or "bid"-prices are set for the resources or units of inventory (seats on flight legs, hotel rooms on specific dates, etc.) and a product (a seat in a fare class on an itinerary or room for a sequence of dates) is sold only if the offered fare exceeds the sum of the threshold prices of all the resources needed to supply the product. This approach is appealing on intuitive and practical grounds, but the theory underlying it is not well developed. Moreover, the extent to which bid-price controls represent optimal or near optimal policies is not well understood. Using a general model of the demand process, we show that bid-price control is not optimal in general and analyze why bid-price schemes can fail to produce correct accept/deny decisions. However, we prove that when leg capacities and sales volumes are large, bid-price controls are asymptotically optimal, provided the right bid prices are used. We also provide analytical upper bounds on the optimal revenue. In addition, we analyze properties of the asymptotically optimal bid prices. For example, we show they are constant over time, even when demand is nonstationary, and that they may not be unique.

/pdf/an-analysis-of-bid-price-controls-for-network-revenue-1n7alsaryb.pdf

An Analysis of Bid-Price Controls for Network Revenue Management

The conventional wisdom that product lifetimes are shrinking has important implications for technology management and product planning. However, very limited empirical informationon this topic is available. In this paper, product lifetimes are directly measured as the time between product introduction and withdrawal. Statistical analyses of desktop personal computer models introduced between 1974 and 1992 are conducted at various product market levels. Results indicate that (1) product technology and product model lifetimes have not accelerated, and (2) manufacturers have not systematically reduced the life-cycles of products within their lines. Instead, the products of firms that have entered this industry in the more recent years tend to be based on previously existing technology, and, not surprisingly, these products have lifetimes that are shorter than those of established firms. Implications of these findings are discussed.

/pdf/an-analysis-of-product-lifetimes-in-a-technologically-zeus2gq2oe.pdf

An Analysis of Product Lifetimes in a Technologically Dynamic Industry

We analyze a randomized version of the deterministic linear programming (DLP) method for computing network bid prices. The method consists of simulating a sequence of realizations of itinerary demand and solving deterministic linear programs to allocate capacity to itineraries for each realization. The dual prices from this sequence are then averaged to form a bid price approximation. This randomized linear programming (RLP) method is only slightly more complicated to implement than the DLP method. We show that the RLP method can be viewed as a procedure for estimating the gradient of the expected perfect information (PI) network revenue. That is, the expected revenue obtained with full information on future demand realizations. The expected PI revenue can, in turn, be viewed as an approximation to the optimal value function. We establish conditions under which the RLP procedure provides an unbiased estimator of the gradient of the expected PI revenue. Computational tests are performed to evaluate the revenue performance of the RLP method compared to the DLP.

/pdf/a-randomized-linear-programming-method-for-computing-network-1zsn0eddts.pdf

Kalyan T. Talluri

Papers

The Theory and Practice of Revenue Management

Revenue Management Under a General Discrete Choice Model of Consumer Behavior

An Analysis of Bid-Price Controls for Network Revenue Management

An Analysis of Product Lifetimes in a Technologically Dynamic Industry

A Randomized Linear Programming Method for Computing Network Bid Prices