In a world going towards automation, I ask whether salespeople making pricing decisions in a high human interaction environment such as business to business (B2B) retail, could be automated, and under what conditions it would be most beneficial. I propose a hybrid approach to automation that combines the expert salesperson and an artificial intelligence model of the salesperson in making pricing decisions in B2B. The hybrid approach preserves individual and organizational knowledge both by learning the expert's decision making behavior and by keeping the expert in the decision making process for decisions that require human judgment. Using sales transactions data from a B2B aluminum retailer, I create an automated version of each salesperson, that learns the salesperson's pricing policy based on her past pricing decisions. In a field experiment, I provide salespeople in the B2B retailer with their own model's price recommendations through their CRM system in real-time, and allow them to adjust their original pricing accordingly. I find that despite the loss of non-codeable information that is available to the salesperson but not to the model, providing the model's price increases profits for treated quotes by as much as 10% relative to a control condition, which translates to approximately $1.3 million in yearly profits. Using a counterfactual analysis, I also find that a hybrid pricing approach, that follows the model's pricing most of time, but defers to the salesperson's pricing when the model is missing important information is more profitable than pure automation or pure reliance on the salesperson's pricing. I find that in most cases the model's scalability and consistency lead to better pricing decisions that translate to higher profits, but when pricing uncommon products or pricing for unfamiliar clients it is best to use human judgment. I investigate different ways, including machine learning methods, to model the salesperson's behavior and to combine salespeople's expertise as reflected by their automated representations, and discuss implications for automation of tasks that involve soft skills.

1. Problem one: Shipment planning in a dynamic environment. The planning of air cargo logistics is a complex endeavor that involves the collaboration of multiple logistics agents to deliver shipments in a timely, safe, and economic manner. Airfreight forwarders coordinate and manage shipments for their clients, and with the development of Internet logistics platforms, airfreight forwarders can now trade jobs and resources with other participants effectively. The incorporation of trading alternatives significantly complicates the shipment planning process. / 2. Problem two: e-services platform design. The need for business logistics starts with a buyer and a seller. It involves arrangements of materials/products moving from the seller to the buyer and payment flows from the buyer and the seller. When the logistics arrangements are not done by the buyer nor the seller but rather by a specialist, we call the specialist a 3rd party logistics (3PL) service providers. A typical logistics service/job involves many agents, for instance, forwarders, truckers, warehouse operators, carriers, etc. In the process, a lot of information will be shared and exchanged among the agents, the buyer and the seller. With the advancement of information technologies, an emerging trend is to have the business dealing, information sharing and even payment arrangement among the logistics agents, buyers and sellers done through e-services on the Internet. In this thesis, we propose a 4th party logistics (4PL) platform, which is an Internet environment to enable and facilitate 3PL providers collaboratively provide services to buyers and sellers. / The proposed platform is called 4PL platform because it facilitates the 3PL agents. To better serve its 3PL clients, the platform should be "neutral", meaning it will not provide logistics services competing with its clients. The 4PL platform will facilitate its clients through e-services. However, existing e-services technology only allows e-services to be provided to individual clients. The idea of providing e-service to collaborating clients is new. We called it the 3rd party e-Service. In this thesis, we have conceptualized and further defined the 3rd party e-Service. To realize the 3rd party e-Service, we have first proposed a 3rd party service-oriented architecture and then developed a set of new elements to the existing e-Service description technology. To prove the concept, the new architecture, and the new description technology, we put into action. Using the shipment planning model as an example, we are able to offer shipment planning e-service to collaborating agents on the Internet. / This dissertation studies two research problems in a 4th party logistics platform. / This study proposes a dynamic decision framework for air cargo shipment planning, within the dynamic environment of bidding and trading. The framework has three phases: estimation, trading, and execution. Planning in the phases proceeds iteratively until an acceptable plan is obtained and shipments are set and fulfilled. The optimization of shipment planning is formulated as a mixed 0-1 LP model from a portfolio point of view. Unlike the models in previous research, this model targets profit maximization and takes into account the decisions of job selection and resource selection, and can be solved using a Tabu-based approach. We also discuss the respective rules and strategies that would aid the decision-making processes in the framework. / Chen Gang. / "February 2006." / Advisers: Waiman Cheung; Chi Kin Leung. / Source: Dissertation Abstracts International, Volume: 67-11, Section: A, page: 4358. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 96-106). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Retaining business value in a legacy commercial enterprise resource planning system today often entails more than just maintaining the software to preserve existing functionality. This type of system tends to represent a significant capital investment that may not be easily scrapped, replaced, or re-engineered without considerable expense. A legacy system may need to be frequently extended to impart new behavior as stakeholder business goals and technical requirements evolve. Legacy ERP systems are growing in prevalence and are both expensive to maintain and risky to evolve. Humans are the driving factor behind the expense, from the engineering costs associated with evolving these types of systems to the labor costs required to operate the result. Autonomic computing is one approach that addresses these challenges by imparting self-adaptive behavior into the evolved system. The contribution of this dissertation aims to add to the body of knowledge in software engineering some insight and best practices for development approaches that are normally hidden from academia by the competitive nature of the retail industry. We present a formal architectural pattern that describes an asynchronous, low-complexity, and autonomic approach. We validate the pattern with two real-world commercial case studies and a reengineering simulation to demonstrate that the pattern is repeatable and agnostic with respect to the operating system, programming language, and communication protocols. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection