Knowledge that Transforms

The widespread implementation of customer relationship management technologies in business has allowed companies to increasingly focus on both acquiring and retaining customers. The challenge of designing incentive mechanisms that simultaneously focus on customer acquisition and customer retention comes from the fact that customer acquisition and customer retention are usually separate but intertwined tasks that make providing proper incentives more difficult. The present study develops incentive mechanisms that simultaneously address acquisition and retention of customers with an emphasis on the interactions between them. The main focus of this study is to examine the impact of the negative effect of acquisition on retention, i.e., the spoiling effect, on firm performance under direct selling and delegation of customer acquisition. Our main finding is that the negative effect of acquisition on retention has a significant impact on acquisition and retention efforts and firm profit. In particular, when the customer acquisition and retention are independent, the firm's profit is higher under direct selling than under delegation; however, when acquisition spoils retention, interestingly, the firm's profit may be higher under delegation. Our analysis also finds that the spoiling effect not only reduces the optimal acquisition effort but may also reduce retention effort under both direct selling and delegation. Comparing the optimal efforts under direct selling and delegation, the acquisition effort is always lower under delegation regardless of the spoiling effect, but the retention effort may be higher under delegation with the spoiling effect. Furthermore, when the customer antagonism effect from price promotions is considered, our main results hold regarding the firm's preferences between direct selling and delegation, which demonstrates the robustness of our model.

We analyze how individuals make forecasts based on time-series data. Using a controlled laboratory experiment, we find that forecasting behavior systematically deviates from normative predictions: Forecasters overreact to forecast errors in relatively stable environments, but underreact to errors in relatively unstable environments. The performance loss that is due to such systematic judgment biases is larger in stable than in unstable environments.

We present the result of research, developed within Nokia Siemens Networks, to solve the downlink sub-frame allocation problem in Mobile WiMAX (IEEE 802.16) technology in its full complexity, while simultaneously fulfilling real-life constraints on processing power and delay. We describe the IEEE 802.16 standard, and introduce two system models. A theoretical analysis of the two-dimensional packing problems originated by such models shows that they are both 𝒩𝒫-hard in the strong sense. From a practical point of view, the processing budget for scheduling in the base station was estimated to be 1 ms on a state-of-the-art PC. Thus, we introduce two highly efficient heuristics that were developed to handle the system practically. A thorough computational analysis of their optimization characteristics and a system-level evaluation in realistic scenarios proved that the algorithms offer significant capacity gain in Mobile WiMAX systems that translate to increased operator revenues.

We examine the effects of mandating the provision of fair value information for long-lived tangible assets on firms' information asymmetry. Specifically, we investigate whether European real estate firms' compulsory adoption of International Accounting Standard 40 (IAS 40; Investment Property), which mandated the provision of investment property fair values in 2005, resulted in reduced information asymmetry across market participants. Using as a control group firms that voluntarily provided these fair values prior to the mandatory adoption of IAS 40, we find that mandatory adoption firms exhibit a larger decline in information asymmetry, as reflected in lower bid–ask spreads. However, we also find that mandatory adoption firms continue to have higher information asymmetry than voluntary adoption firms, which appears partially attributable to the lower reliability of fair values reported by the mandatory adoption firms. Together, this evidence adds to the debate on fair value accounting by demonstrating that common adoption of fair value, even for long-lived tangible assets, under a mandatory reporting regime can reduce, but not necessarily eliminate, information asymmetry differences across firms.

We study markets for information goods and find that they differ significantly from markets for traditional industrial goods. Markets for information goods in which products are vertically differentiated lack the segmentation inherent in markets for industrial goods. As a result, a monopoly will offer only a single product. Competition leads to highly concentrated information-good markets, with the leading firm behaving almost like a monopoly even with free entry and without network effects. We study how the structure of the firms' cost functions drives our results.

This paper presents a new implicit formulation for shift scheduling problems, using context-free grammars to model the rules for the composition of shifts. From the grammar, we generate an integer programming (IP) model having a linear programming relaxation equivalent to that of the classical set covering model. When solved by a state-of-the-art IP solver on problem instances with a small number of shifts, our model, the set covering formulation, and a typical implicit model from the literature yield comparable solution times. On instances with a large number of shifts, our formulation shows superior performance and can model a wider variety of constraints. In particular, multiactivity cases, which cannot be modeled by existing implicit formulations, can easily be handled with grammars. We present comparative experimental results on a large set of instances involving one work activity, as well as on problems dealing with up to 10 work activities.

We analyze the computational problem of estimating financial risk in a nested simulation. In this approach, an outer simulation is used to generate financial scenarios, and an inner simulation is used to estimate future portfolio values in each scenario. We focus on one risk measure, the probability of a large loss, and we propose a new algorithm to estimate this risk. Our algorithm sequentially allocates computational effort in the inner simulation based on marginal changes in the risk estimator in each scenario. Theoretical results are given to show that the risk estimator has a faster convergence order compared to the conventional uniform inner sampling approach. Numerical results consistent with the theory are presented.

This article analyzes the relationship between organizational change and employee health. It illuminates the potentially negative outcomes of change at the level of the employee. In addition, it relates to the ongoing debate over how employees react to and respond to organizational change. I hypothesize that change increases the risk of negative stress, and I test this hypothesis using a comprehensive panel data set of all stress-related medicine prescriptions for 92,860 employees working in 1,517 of the largest Danish organizations. The findings suggest that the risk of receiving stress-related medication increases significantly for employees at organizations that change, especially those that undergo broad simultaneous changes along several dimensions. Thus, organizational changes are associated with significant risks of employee health problems. These effects are further explored with respect to employees at different hierarchical levels as well as at firms of different sizes and from different sectors.

When learning of product characteristics takes some time, a firm introducing a new durable faces the trade-off between releasing early to an uninformed market and deferring release to a better-informed market. In a two-period monopoly, we examine the strategic interaction between exogenous learning (EL) and seller-induced learning (SIL) and the firm's product release and pricing strategies. The familiar, direct effect of strong learning is to facilitate a higher price for informed customers. We point out its indirect effect of inducing a higher period 1 price for uninformed customers (by lowering their expected utility from learning). These two effects underlie three major results. First, a strong learning intensity does not always imply deferred release. Surprisingly, for medium unit costs, the firm releases late (early) when learning intensity is weak (strong). Second, SIL facilitates different product release strategies, depending on the unit cost level. Potential SIL investment facilitates early release for low or medium unit costs, but may facilitate deferred release for high unit costs. Lastly, when customers have heterogeneous prior valuation, the high-end customers may buy early at a lower price and the low-end customers may buy later at a higher price, contrary to the usual skim pricing with informed customers.

Science and technology advances drive firms to continually enhance their product's performance and launch sequentially improving offerings. Firms face challenges in marketing such improving products to well-informed, forward-looking consumers who anticipate product improvements and seek to delay their purchase timing. Product design, specifically a modular upgradable architecture in which improving and stable subsystems of a product are separated and selectively upgraded, can be a valuable approach for marketers to alleviate consumer concerns about product obsolescence. However, such an architecture-based approach can present new challenges as well, and dealing with them requires carefully coordinated cross-functional decision making by the firm. In this paper, we identify and formalize the notion of design inconsistency, which refers to the monopolist firm's inability to commit to future product design architectures. We find that firms experience design inconsistency even when they are able to commit to future prices, and design inconsistency lowers firm profits as well as consumer surplus. We then derive a joint product architecture and pricing approach to solve this problem; this enables an innovating firm to optimally and in a time-consistent manner launch modular upgradable products. The modeling and analysis in the paper lends insight into types of markets and products for which modular upgradability is most appropriate and offers guidelines on making pricing and product design decisions jointly for managing sequential innovation.