Despite the increased importance of services in the manufacturing sector, the academic literature is yet to investigate the many questions that arise under this new manufacturing paradigm. Perhaps for the same reason study of servitization is listed as a research priority in recent publications both in the field of service operations management and in the field services marketing. This dissertation covers three essays aimed at disentangling multiple aspects of the role of services in the manufacturing sector. The literature on the drivers and implications of transition towards services in manufacturing firms is limited. The three studies in this dissertation aim at shedding light on this issue.
Specifically, the first essay looks at the innovation benefits of service transactions with customers. This paper demonstrate the value of services in getting manufacturers closer to customers and allowing them glean useful information from their service interactions. The second essay investigates the antecedents of service strategy adoption. We suggest that the extant diversification theory does not fully explain servitization and this phenomenon represents a unique type of diversification, which is likely driven by different factors. Through econometric analysis of financial data over a 27-year period, this study explores characteristics of product, firm resources, competition, and industry that encourage adoption of service strategies in manufacturing sector. Finally, the third essay takes a deeper dive and focuses on dealerships, as service centers, in the automobile industry. It investigates the role of dealerships in the success of automakers and explores dealership traits that are critical for market success of an automobile brand.
The novel Coronavirus Disease 2019 exposed issues in the supply chain for N95 face masks. The demand for protective face masks spiked globally and domestically due to the unexpected outbreak of the pandemic. An important issue was the dependency on N95 mask production in countries abroad. The focus on face masks in this thesis accounts for all models of the N95 mask.<br/>This thesis will focus on onshore and offshore production of N95 face masks before and during the pandemic. Specifically, we will focus on (1) the production of masks in 2019; (2) 3M, Honeywell, and Prestige Ameritech’s production changes; (3) the observations made by All The Things LLC, a broker for face masks; (4) the rise of counterfeit masks and actions taken to stop counterfeit production; (4) actions taken by the federal government to aid in production and distribution; and (5) future research opportunities on this topic. This research project into the production of N95 face masks ceased in February of 2021. <br/>This thesis defends the critical need for more domestically produced N95 masks. The U.S. needs to increase the number of N95 masks produced domestically, manage the Strategic National Stockpile to eliminate masks past their shelf life, and create a plan to replenish the stockpile to reduce the possibility of a shortage when the next public health emergency takes place.
The CDS model and methodologies are integrated into an architecture using concepts from cognitive computing. The proposed architecture is implemented with an example use case to inventory management.
Reinforcement learning (RL) is discussed as an alternative, generalized adaptive learning engine for the CDS system to handle the complexity of many problems with unknown environments. An adaptive state dimension with context that can increase with newly available information is discussed. Several enhanced components for RL which are critical for complex use cases are integrated. Deep Q networks are embedded with the adaptive learning methodologies and applied to an example supply chain management problem on capacity planning.
A new approach using Ito stochastic processes is proposed as a more generalized method to generate non-stationary demands in various patterns that can be used in decision problems. The proposed method generates demands with varying non-stationary patterns, including trend, cyclical, seasonal, and irregular patterns. Conventional approaches are identified as special cases of the proposed method. Demands are illustrated in realistic settings for various decision models. Various statistical criteria are applied to filter the generated demands. The method is applied to a real-world example.
As our discipline has matured, we have begun to develop theories of supply chain management. However, we submit that a major omission of theory development in the supply chain management discipline is that we have failed to develop a theory of what we are managing - a theory of the supply chain. Using a conceptual theory building approach, we introduce foundational premises about the structure and boundary of the supply chain, which can serve as the basis for much needed, additional development of the theory of the supply chain.