Essays on Corporate Diversification

This thesis consists of three empirical essays on corporate diversification. The first empirical study (Chapter 2) examines the relationship between coinsurance across divisional investment opportunities and the value of corporate cash holdings. The study finds that coinsurance across divisional investment opportunities reduces the value of cash for poorly governed firms and constrained firms, but increases the value of cash for firms with efficient internal capital markets. Evidence suggests that the agency channel dominates the other two, leading to an overall negative effect of coinsurance across divisional investment opportunities on the marginal value of cash. The second empirical study (Chapter 3) examines the impact of coinsurance across divisional investment opportunities on merger outcomes. The study finds that coinsurance across divisional investment opportunities is negatively associated with acquirer announcement returns and post-merger operating performance. The study documents a positive link between coinsurance across divisional investment opportunities and the probability of firms initiating mergers when they are poorly-governed. Evidence suggests that coinsurance across divisional investment opportunities is closely associated with agency problems and thus can lead to value destruction in diversified firms. The third empirical study (Chapter 4) examines the impact of product market competition on the relationship between corporate diversification and the cost of debt financing. The study finds that that product market competition amplifies the cost-reduction benefits of diversification for financially constrained firms and firms with efficient internal capital markets, but it can reduce the diversification benefits for firms with a high level of multimarket contacts. Although intense competition may, in some cases, undermine the tacit collusion through the multimarket contacts in diversified firms, overall, the negative association between diversification and cost of debt financing is stronger in firms facing intense competition. Evidence suggests that the diversification benefits in the debt market, to some extent, alleviate the negative effect of diversification in the equity market

Developing Fairness Rules for Talent Intelligence Management System

Talent management is an important business strategy, but inherently expensive due to the unique, subjective, and developing nature of each talent. Applying artificial intelligence (AI) to analyze large-scale data, talent intelligence management system (TIMS) is intended to address the talent management problems of organizations. While TIMS has greatly improved the efficiency of talent management, especially in the processes of talent selection and matching, high-potential talent discovery and talent turnover prediction, it also brings new challenges. Ethical issues, such as how to maintain fairness when designing and using TIMS, are typical examples. Through the Delphi study in a leading global AI company, this paper proposes eight fairness rules to avoid fairness risks when designing TIMS

Large-scale Google Street View Images for Urban Change Detection

Urbanization has entered a new phase characterized by urban changes occurring at a micro-scale and “under the roof”, as opposed to external modifications. These changes, known as urban retrofitting, involve the incorporation of novel technologies or features into pre-existing systems to promote sustainability. Given the limitations of remote sensing images in identifying such urban changes, novel tools need to be developed for detecting urban retrofitting. In this study, we first build a pipeline to collect large-scale time-series urban street view images from Google Street View in Mecklenburg County, North Carolina. And we examine the feasibility of utilizing the acquired dataset to detect diverse forms of urban retrofitting, including re-building, re-greening and re-capital

Health Monitoring of Metallic Structures with Electromechanical Impedance and Piezoelectric Sensors.

In order to monitor the health condition of structures in a more sensitive and accurate way, a novel and universal methodology called direct coupling mechanical impedance (DCMI) for characteristic signatures extraction is presented in this paper. This methodology is used to obtain DCMI signatures from measured raw signatures (RSs) with the surface-bonded piezoelectric sensors (PZT), which is developed from a pertinent electromechanical impedance (EMI) theoretical model for surface-bonded circular PZT. The proposed DCMI methodology has the advantages of simple calculation and magnifying the signatures when compared with the existing methods. Combining the extracted DCMI signatures with the root mean square deviation (RMSD) index is able to quantify the correlation between the health condition and the signatures variation more effectively. To verify the effectiveness of proposed DCMI methodology, experiments are conducted on aluminum plates and a part of fuselage in detail. The experimental results sufficiently demonstrate that the presented universal DCMI methodology possesses better sensitivity than the raw signatures when utilized for evaluating the health condition of metallic structures, including those made of metal-matrix nanomaterials

Monitoring of Fiber-Reinforced Composite Single-Lap Joint with Electromechanical Impedance of Piezoelectric Transducer.

The single-lap joint of fiber-reinforced composites is a common structure in the field of structure repair, which has excellent mechanical properties. To study and monitor its quasi-static response behavior under external load, two methodologies called effective structural mechanical impedance (ESMI) and reduced-ESMI (R-ESMI) are presented in this article. A two-dimensional electromechanical impedance (EMI) model for a surface-bonded square piezoelectric transducer (PZT) is adopted to extract more sensitive signatures from the measured raw signatures. There are two major advantages of the monitoring scheme based on ESMI and R-ESMI signatures: (1) excellent monitoring results with less signatures to process, (2) the ability to monitor the quasi-static behavior of a single-lap joint with previously ignored susceptance signatures. Combining the extracted ESMI signatures with the index of root-mean-square deviation, the quasi-static behavior of single-lap joints can be effectively quantified. To test the effectiveness of ESMI methodology, verifying experiments were conducted. The experimental results convincingly demonstrated that the presented ESMI and R-ESMI methodologies have good feasibility in monitoring the quasi-static behavior of a fiber-reinforced composite single-lap joint. The proposed method has potential application in the field of structural health monitoring (SHM)

Evaluation of Genetic Susceptibility Loci for Chronic Hepatitis B in Chinese: Two Independent Case-Control Studies

BACKGROUND: A recent genome-wide scan has identified two genetic variants in the HLA-DP region strongly associated with hepatitis B infection in Japanese. This study evaluates the effects of these risk variants in Chinese, where the HBV infection is the most popular in the world. METHODS AND FINDINGS: We have assessed the relationship between these two single nucleotide polymorphisms (rs3077 and rs9277535) and chronic hepatitis B infection in two independent case-control studies. The first population in Chinese Han included 736 patients and 782 spontaneously recovered controls. The second set was established in Chinese Zhuang minority of 177 patients and 208 controls. Both A alleles of rs3077 and rs9277535 significantly deceased the risk to CHB in Chinese Han (OR = 0.540, 95%CI: 0.464-0.628, P = 4.068×10(-16) and OR = 0.696, 95%CI: 0.601-0.806, P = 1.062×10(-6), respectively). Conceivably, rs9277535 was found to be associated with decreased risk of the disease in Chinese Zhuang, with an OR of 0.606 (95%CI, 0.441-0.833, P = 0.002). CONCLUSION: Chronic hepatitis B susceptibility loci in HLA-DP region (rs3077 and rs9277535) identified by genome-wide scan in Japanese population were validated in Chinese population. These findings might provide clues to develop screening and surveillance strategies

Konsensusalgoritmer i Blockchain : En undersökning för att skapa beslutsträd för blockchain-applikationer

Blockchain is a decentralized database that is distributed among a computer network. To enable a smooth decision making process without any authority, different blockchain applications use their own consensus algorithms. The problem is that for a new blockchain application, there is limited aid in deciding which algorithm it should implement. Selecting consensus algorithms is crucial because reaching consensus is the fundamental issue of a decentralized system. Different algorithms are designed with their own advantages and limitations, making it complex to navigate one’s way through a list of consensus algorithms. This thesis attempts to contribute to solving this problem by surveying 15 existing cryptocurrencies’ consensus algorithms used in their blockchain application and then producing a decision tree as the aid for algorithm selection. The top 5 algorithms from each category in Proof of Work (PoW), Proof of Stake (PoS), and Hybrid Proof of Work + Proof of Stake (PoW + PoS) are selected. The research method is qualitative. The study shows that different consensus algorithms often share some properties, but they are usually built to solve the issues of another algorithm, which means they also have their own distinctive advantages. Therefore, the decision tree reveals how these algorithms are logically connected and the key properties blockchain consensus algorithms possess. Based on the result of this thesis, further research can be conducted to include more algorithms in order to make the decision tree more comprehensive. Implementations of these algorithms in similar network setup can also be done to experiment with their claimed properties. The decision tree can be sent to industry for further feedback.Blockchain är en decentraliserad databas som distribueras i ett datornätverk. För att möjliggöra en smidig beslutsprocess utan någon auktoritet använder olika blockkedjeapplikationer sina egna konsensusalgoritmer. Problemet är att för en ny blockchain-applikation finns det begränsad hjälp för att bestämma vilken algoritm den ska implementera. Att välja konsensusalgoritmer är avgörande eftersom att nå konsensus är den grundläggande frågan för ett decentraliserat system. Olika algoritmer är designade med sina egna fördelar och begränsningar, vilket gör det komplicerat att navigera sig igenom en lista med konsensusalgoritmer. Forskningsmetoden är kvalitativ. Det här dokumentet försöker bidra till att lösa detta problem genom att kartlägga 15 befintliga kryptovalutors konsensusalgoritmer som används i deras blockkedjeapplikation och sedan ta fram ett beslutsträd som hjälp för val av algoritmer. De 5 bästa algoritmerna från varje kategori i Proof of Work (PoW), Proof of Stake (PoS) och Hybrid Proof of Work + Proof of Stake (PoW + PoS) väljs. Studien visar att olika konsensusalgoritmer ofta delar vissa egenskaper, men de är vanligtvis byggda för att lösa problem med en annan algoritm, vilket innebär att de också har sina egna distinkta fördelar. Därför avslöjar beslutsträdet hur dessa algoritmer är logiskt kopplade och de nyckelegenskaper som blockchain konsensusalgoritmer besitter. Baserat på resultatet av denna artikel kan ytterligare forskning utföras för att inkludera fler algoritmer för att göra beslutsträdet mer heltäckande. Implementeringar av dessa algoritmer i liknande nätverksuppsättningar kan också göras för att experimentera med deras påstådda egenskaper. Beslutsträdet kan skickas till industrin för vidare feedback

Konsensusalgoritmer i Blockchain : En undersökning för att skapa beslutsträd för blockchain-applikationer

Blockchain is a decentralized database that is distributed among a computer network. To enable a smooth decision making process without any authority, different blockchain applications use their own consensus algorithms. The problem is that for a new blockchain application, there is limited aid in deciding which algorithm it should implement. Selecting consensus algorithms is crucial because reaching consensus is the fundamental issue of a decentralized system. Different algorithms are designed with their own advantages and limitations, making it complex to navigate one’s way through a list of consensus algorithms. This thesis attempts to contribute to solving this problem by surveying 15 existing cryptocurrencies’ consensus algorithms used in their blockchain application and then producing a decision tree as the aid for algorithm selection. The top 5 algorithms from each category in Proof of Work (PoW), Proof of Stake (PoS), and Hybrid Proof of Work + Proof of Stake (PoW + PoS) are selected. The research method is qualitative. The study shows that different consensus algorithms often share some properties, but they are usually built to solve the issues of another algorithm, which means they also have their own distinctive advantages. Therefore, the decision tree reveals how these algorithms are logically connected and the key properties blockchain consensus algorithms possess. Based on the result of this thesis, further research can be conducted to include more algorithms in order to make the decision tree more comprehensive. Implementations of these algorithms in similar network setup can also be done to experiment with their claimed properties. The decision tree can be sent to industry for further feedback.Blockchain är en decentraliserad databas som distribueras i ett datornätverk. För att möjliggöra en smidig beslutsprocess utan någon auktoritet använder olika blockkedjeapplikationer sina egna konsensusalgoritmer. Problemet är att för en ny blockchain-applikation finns det begränsad hjälp för att bestämma vilken algoritm den ska implementera. Att välja konsensusalgoritmer är avgörande eftersom att nå konsensus är den grundläggande frågan för ett decentraliserat system. Olika algoritmer är designade med sina egna fördelar och begränsningar, vilket gör det komplicerat att navigera sig igenom en lista med konsensusalgoritmer. Forskningsmetoden är kvalitativ. Det här dokumentet försöker bidra till att lösa detta problem genom att kartlägga 15 befintliga kryptovalutors konsensusalgoritmer som används i deras blockkedjeapplikation och sedan ta fram ett beslutsträd som hjälp för val av algoritmer. De 5 bästa algoritmerna från varje kategori i Proof of Work (PoW), Proof of Stake (PoS) och Hybrid Proof of Work + Proof of Stake (PoW + PoS) väljs. Studien visar att olika konsensusalgoritmer ofta delar vissa egenskaper, men de är vanligtvis byggda för att lösa problem med en annan algoritm, vilket innebär att de också har sina egna distinkta fördelar. Därför avslöjar beslutsträdet hur dessa algoritmer är logiskt kopplade och de nyckelegenskaper som blockchain konsensusalgoritmer besitter. Baserat på resultatet av denna artikel kan ytterligare forskning utföras för att inkludera fler algoritmer för att göra beslutsträdet mer heltäckande. Implementeringar av dessa algoritmer i liknande nätverksuppsättningar kan också göras för att experimentera med deras påstådda egenskaper. Beslutsträdet kan skickas till industrin för vidare feedback

Effect of tocopherols incorporation on physical properties of LDPE,PP and blend film of LDPE/PP

The objectives of this study were to investigate the effects of added tocopherols and blending of different polymers on the film physical properties.Tocopherols (3 000 mg/kg) were incorporate into low density polyethylene (LDPE),polypropylene (PP) and a blend film of LDPE/PP (50/50) by extrusion process.Then films were evaluated to determine tocopherol recovery and physical properties.Results showed that extrusion did not significantly change film thermal properties (Tm,Tc and Tg) as compared with synthetic polymer resin pellet (raw material).LDPE and PP did not seem to react with each other to form new polymers under the current extrusion conditions.Addition of tocopherol significantly changed film mechanical properties compared with control.The above results and other data seemed to support that polymer blending is a feasible approach for producing tocopherol containing packaging films

Effects of Centralized and Distributed Quality Control on Sales of Experience Goods in a Transaction Platform Ecosystem

Platform-based ecosystems attract diverse independent sellers and buyers to trade products or services. As such transaction platform ecosystems grow, the quality of the goods sold in these ecosystems may vary increasingly, leading possibly to customer dissatisfaction, declining sales, or even the collapse of the whole ecosystems. In this study, we examine two governance mechanisms that can help control the quality of the goods sold in transaction platform ecosystems: centralized control by the platform owners and distributed control by platform participants. Data collected on international package tours at Trip.com indicates that both centralized control (e.g., platform-assessed quality ratings) and distributed control (e.g., customer-generated quality ratings) can boost sales. Further analysis suggests that centralized control complements distributed control and their relative effectiveness reverses when the volume of customer reviews changes. Therefore, the study expands the concept of distributed governance from its original focus on decision rights partitioning to the realm of control portfolio configuration, where the platform owner, sellers, and buyers can jointly control product quality, so that sales can grow and platform ecosystems can thrive