Flexibility and Cost in Information Technology Outsourcing: Balancing Opposing Goals

The growth in the importance of IT outsourcing arrangements combined with the rate of failure of such arrangements makes it imperative to address issues of contracting in the IS literature. In this work, we examine the contract directly and show how the costs stipulated in the contract affect the nature of the outsourcing relationship. The work develops a mathematical model of IT outsourcing contracts to explore the relationship between costs of the anticipated IT needs and the costs of additional resources in the face of changing IT needs. The model exposes the underlying tension between the baseline cost of an anticipated bundle of services and the flexibility to modify that bundle in response to changing environmental conditions. Additionally, we draw testable propositions about the relationship between contractually specified costs of IT services and the costs inherent in both client and vendor production of IT services. The model shows that client can never get the same cost structure as the vendor. Rather the client achieves contractually specified cost structure that will be a compromise between vendor and client costs. The model also proposes that contractual flexibility is directly related to the contractually specified cost of the anticipated bundle of IT services. Thus, contracts that stipulate a very low baseline cost for the anticipated bundle of IT services are less flexible so that changes beyond the baseline are more expensive

Material force approach for tire durability analysis

by Param Punj SinghM.Tech

Jack of All, Master of Some: The Contingent Effect of Knowledge Breadth on Innovation

This study investigates how individuals’ knowledge structure affects their new product ideation outcome. Because individuals who possess diverse knowledge can potentially create more novel recombination, broad knowledge has been touted as the key driver of innovation. Yet, a shallow grasp of a wide array of knowledge might be sufficient to generate novel ideas but are insufficient to produce innovative ideas that should also be useful and economically feasible. Deep knowledge complements broad knowledge by aiding individuals to effectively combine diverse set of knowledge and to identify constraints of potential solutions. Consequently, individuals with both broad and deep knowledge are expected to outperform those who only possess broad knowledge in innovation tasks. Our findings in a new product idea crowdsourcing community are consistent with our predictions: knowledge breadth feeds into novelty of ideas, but its effect on usefulness and innovativeness of ideas is contingent on the presence of deep knowledge

CROWDSOURCING “BLOCKBUSTER” IDEAS: A DYNAMIC STRUCTURAL MODEL OF IDEATION

Crowdsourcing is becoming an increasing popular tool for new idea generation for firms but the number of ideas generated often decline over time and the implementation rates are very low. Critics of crowdsourcing often attribute these observations to users’ restrictive view about firms’ products leading to contribution of mainly niche ideas, and limited knowledge about firms’ cost structure leading to contribution of mostly infeasible ideas. Using a rich dataset obtained from Ideastorm.com, which is a crowdsourcing website affiliated with Dell, we find that individuals tend to significantly underestimate firm\u27s costs of implementation of their ideas but overestimate the potential of their ideas in the beginning of the their idea contribution history. However, individuals learn very quickly about their abilities to come up with high potential ideas but the learning regarding the firm\u27s cost structure is quite slow. As a result of the learning process, contributors of low potential ideas eventually drop out, and high potential idea contributors remain active

Crowdsourcing Contests: A Dynamic Structural Model of the Impact of Incentive Structure on Solution Quality

A key challenge faced by firms that undertake crowdsourcing-contests to get solutions from crowds to their problems is to design an incentive structure which helps attract high quality solutions. We develop a structural model of user participation in crowdsourcing-contests and present empirical evidence on how incentive structure could affect the quality of solutions. Using data from Threadless.com, we find that participants exert less effort as competition for the reward increases. This may indicate that increasing the reward may adversely affect the quality of the solutions produced as it will increase the competition. However, counter-intuitively the policy simulations indicate that increasing the reward increases both quantity and quality of the solutions. This is because under the new policy of higher reward, individual equilibrium behavior is different. When the firm increases the reward, the additional utility from increase in the reward offsets the reduction in probability of winning due to intensified competition

Forgotten Third Parties: Analyzing the Contingent Association Between Unshared Third Parties, Knowledge Overlap, and Knowledge Transfer Relationships with Outsiders

Third parties play a prominent role in network-based explanations for successful knowledge transfer. Third parties can be either shared or unshared. Shared third parties signal insider status and have a predictable positive effect on knowledge transfer. Unshared third parties, however, signal outsider status and are believed to undermine knowledge transfer. Surprisingly, unshared third parties have been ignored in empirical analysis, and so we do not know if or how much unshared third parties contribute to the process. Using knowledge transfer data from an online technical forum, we illustrate how unshared third parties affect the rate at which individuals initiate and sustain knowledge transfer relationships. Empirical results indicate that unshared third parties undermine knowledge sharing, and they also indicate that the magnitude of the negative unshared-third-party effect declines the more unshared third parties overlap in what they know. Our results provide a more complete view of how third parties contribute to knowledge sharing. The results also advance our understanding of network-based dynamics defined more broadly. By documenting how knowledge overlap among unshared third parties moderates their negative influence, our results show when the benefits provided by third parties and by bridges (i.e., relationships with outsiders) will be opposed versus when both can be enjoyed