The impact of information technology on vertical relationships

textThis dissertation has three parts that study the impact of information technology on competition and vertical relationships from different perspectives. The first part focuses on an electronic market where product information is important for consumers to identify their ideal product and the Internet greatly reduces consumers’ search cost. The model studies how reduced search cost influences social welfare and retailers’ incentive to provide product information. It is found that if technology reduces consumers’ search cost to evaluate products and compare prices, sellers who invest in providing valuable information may not be able to recover their investments. Therefore, by lowering sellers’ incentive to prov vide product information, reduced search cost may negatively impact social welfare as consumers have to search more to identify their ideal product. The study also shows that sellers need to develop the capability of, and reputation for, information provision in order to make profits, even though some consumers and sellers may free ride. The second part extends the first model. In the second model, the manufacturer decides whether to distribute products through the electronic or the physical channel, or through both the channels. In the model, different channels have different search costs for consumers, different abilities to offer product information, and different reach to consumers. The model suggests that the manufacturer uses both the channels when product information is very valuable and product information is largely about digital attributes, or when the product information is not valuable. The model also suggests that when the manufacturer chooses to sell through both the channels the manufacturer need not sell through the most well-known electronic retailer. This part also discusses the case where the manufacture is vertically integrated. That is, the manufacturer itself operates in one of the channels. The third part continues the second part and focuses on firms’ vertical integration (VI) strategy. It examines firms included in 1995-1997 InformationWeek 500 and COMPUSTAT database to study the impact of competitive environment on how IT affects the level of vertical integration. It is found that the competitive environment moderates the impact of IT on vertical integration - in more dynamic environments IT is associated with a decrease in VI, and in more stable environments IT is associated with an increase in VI.Information, Risk, and Operations Management (IROM

Industry Productivity Growth: A Network Perspective

Background: This study investigates the determinants of industrial productivity growth from a network perspective. Objectives: The research focuses on the influence on a focal industry’s productivity growth by its partner industries’ productivity growth, and the impact of the focal industry’s position in the supply chain network. Method/Approach: The paper models the economy as a customer-supplier industry network and empirically investigates how a focal industry’s multifactor productivity is influenced by the productivities of industries that are connected to it, and how this influence is moderated by its position in the network. Results: Based on a balanced panel dataset of 55 industries from the United States Bureau of Economic Analysis (BEA) input-output accounts, the results indicate that a focal industry’s productivity growth is positively associated with its partner industries’ productivity growth, and that industries with higher centrality in the network tend to have higher productivity growth. Conclusions: The study concludes with a discussion on the implications of the findings and the contribution to the productivity literature. Several directions for further research were identified

Cloud-Based Design and Manufacturing Systems: A Social Network Analysis

Cloud-Based Design and Manufacturing (CBDM) System refers to an information and communication technology (ICT) system that facilitates design and manufacturing knowledge sharing between actors (e.g., CBDM service providers and consumers) in the distributed and collaborative socio-technical network. The aim of this study is to address the challenge of information sharing and technical communication during the CBDM product development process. Specifically, we model a CBDM system as a socio-technical network. The research questions are: (1) What measures can be used to analyze the socio-technical network generated by CBDM? (2) How to detect communities/clusters and key actors in the socio-technical network? To answer these questions, a social network analysis (SNA) approach is formulated to analyze the socio-technical network generated by CBDM systems. The results indicate that SNA allows for visualizing collaborative relationship patterns of actors as well as detecting the community structure of CBDM systems

Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation

Cloud-based design manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are enabled to configure, select, and utilize customized product realization resources and services ranging from computer-aided engineering software to reconfigurable manufacturing systems. An ongoing debate on CBDM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, communication and collaboration processes, crowdsourcing processes, information and communication infrastructure, programming models, data storage, and new business models pertaining to CBDM. One question, in particular, has often been raised: is cloud-based design and manufacturing actually a new paradigm, or is it just ‘‘old wine in new bottles’’? To answer this question, we discuss and compare the existing definitions for CBDM, identify the essential characteristics of CBDM, define a systematic requirements checklist that an idealized CBDM system should satisfy, and compare CBDM to other relevant but more traditional collaborative design and distributed manufacturing systems such as web- and agent-based design and manufacturing systems. To justify the conclusion that CBDM can be considered as a new paradigm that is anticipated to drive digital manufacturing and design innovation, we present the developmentof a smart delivery drone as an idealized CBDM example scenario and propose a corresponding CBDM system architecture that incorporates CBDM-based design processes, integrated manufacturing services, information and supply chain management in a holistic sense

Cloud-Based Manufacturing: Old Wine in New Bottles?

AbstractCloud-based manufacturing (CBM), also referred to as cloud manufacturing, is a form of decentralized and networked manufacturing evolving from other relevant manufacturing systems such as web- and agent-based manufacturing. An ongoing debate on CBM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, programming models, file systems, operational processes, information and communication models, and new business models pertaining to CBM. One question, in particular, has often been raised: Is cloud-based manufacturing a new paradigm, or is it just old wine in new bottles? Based on the discussion of the key characteristics of CBM, the derivation of requirements that an ideal CBM system should satisfy, and a thorough comparison between CBM and other relevant manufacturing systems, we provide supporting evidence that allows us to conclude that CBM is definitely a new paradigm that will revolutionize manufacturing

Cloud Manufacturing: Strategic Vision and State-of-the-Art

Cloud manufacturing, a service oriented, customer centric, demand driven manufacturing model is explored in both its possible future and current states. A unique strategic vision for the field is documented, and the current state of technology is presented from both industry and academic viewpoints. Key commercial implementations are presented, along with the state of research in fields critical to enablement of cloud manufacturing, including but not limited to automation, industrial control systems, service composition, flexibility, business models, and proposed implementation models and architectures. Comparison of the strategic vision and current state leads to suggestions for future work, including research in the areas of high speed, long distance industrial control systems, flexibility enablement, business models, cloud computing applications in manufacturing, and prominent implementation architectures

Sequence Stratigraphy of Fine-Grained “Shale” Deposits: Case Studies of Representative Shales in the USA and China

The fine-grained “shale” deposits host a vast amount of unconventional oil and gas resources. This chapter examines the variations in lithofacies, patterns of well logs, geochemistry, and mineralogy in order to construct a sequence stratigraphic framework of the representative marine Barnett, Woodford, Marcellus, Mowry, and Niobrara fine-grained “shales” (USA) and the marine Longmaxi shale and lacustrine Chang7 lacustrine shale (China). Practical methods are proposed in order to recognize the sequence boundaries, the flooding surfaces, the parasequences and parasequence sets, the system tracts, and variation patterns of facies and rock properties. The case studies for the sequence stratigraphy in the USA and China have revealed that the transgressive systems tract (TST) and the early highstand systems tract (EHST, if identifiable) of fine-grained “shales” have been deposited in anoxic settings. TST and EHST of the siliciclastic “shales” are characterized by high gamma ray, high TOC, and high quartz content, while TST and EHST of the carbonate-dominated fine-grained “shales” are characterized by low gamma ray, organic lean, and carbonate rich fine-grained deposits. The lithofacies, geochemistry, mineralogy, depositional evolution, and reservoir development have been predicted and correlated within a sequence stratigraphic framework for the suggested cases. The best reservoir with the best completion quality is developed in TST and HST in both siliciclastic-dominated and carbonate-dominated fine-grained “shales.

Subhealth: definition, criteria for diagnosis and potential prevalence in the central region of China

BACKGROUND: A full evaluation of health conditions is necessary for the effective implementation of public health interventions. However, terms to address the intermediate state between health and disease are lacking, leading the public to overlook this state and thus increasing the risks of developing disease. METHODS: A cross-sectional health survey of 1,473 randomly recruited Chinese Han adults of both sexes living in the central region of China. The criteria for diagnosis of subhealth was defined as the presence of ≥ 1 of the following abnormalities: body mass index ≥ 25 kg/m(2) or waist circumference ≥ 102 cm in men and 88 cm in women; systolic pressure 120–139 mmHg and/or diastolic pressure 80–89 mmHg; serum triglyceride level ≥ 150 mg/dL and/or total cholesterol level ≥ 200 mg/dL and/or high-density lipoprotein cholesterol level < 40 mg/dL in men and 50 mg/dL in women; serum glucose level 110–125 mg/dL; estimated glomerular filtration rate 60–89 ml/min/1.73 m(2); levels of liver enzymes in liver function tests between 41–59 U/L, or with fatty liver disease but < 33% of affected hepatocytes; levels of oxidative stress biomarkers beyond the reference range of 95%; or problems with both sleep quality and psychological state. RESULTS: The prevalences of subhealth and disease in the central region of China were 36.6% and 43.1%, respectively. The prevalence of disease increased from 26.3% in participants aged 20–39 years, to 47.6% and 78.9% for participants aged 40–59 years and those aged 60 years or older, respectively. Compared with participants aged 20–39, the prevalences of health and subhealth in participants aged 60 years or older decreased by 86.7% and 60.3%, respectively. The prevalence of subhealth was increased in association with increases in lifestyle risk scores, while the prevalences of both health and disease were reduced. CONCLUSION: The prevalences of subhealth and disease are high in central China. Subhealth is associated with high lifestyle risk scores. Both the health care sector and the public should pay more attention to subhealth. Lifestyle modifications and/or psychological interventions are needed to ameliorate these conditions

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

Manufacturers have faced an increasing need for the development of predictive models that predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or components. Classical model-based or physics-based prognostics often require an in-depth physical understanding of the system of interest to develop closedform mathematical models. However, prior knowledge of system behavior is not always available, especially for complex manufacturing systems and processes. To complement model-based prognostics, data-driven methods have been increasingly applied to machinery prognostics and maintenance management, transforming legacy manufacturing systems into smart manufacturing systems with artificial intelligence. While previous research has demonstrated the effectiveness of data-driven methods, most of these prognostic methods are based on classical machine learning techniques, such as artificial neural networks (ANNs) and support vector regression (SVR). With the rapid advancement in artificial intelligence, various machine learning algorithms have been developed and widely applied in many engineering fields. The objective of this research is to introduce a random forests (RFs)-based prognostic method for tool wear prediction as well as compare the performance of RFs with feed-forward back propagation (FFBP) ANNs and SVR. Specifically, the performance of FFBP ANNs, SVR, and RFs are compared using an experimental data collected from 315 milling tests. Experimental results have shown that RFs can generate more accurate predictions than FFBP ANNs with a single hidden layer and SVR