Risk assessment and relationship management: practical approach to supply chain risk management

The literature suggests the need for incorporating the risk construct into the measurement of organisational performance, although few examples are available as to how this might be undertaken in relation to supply chains. A conceptual framework for the development of performance and risk management within the supply chain is evolved from the literature and empirical evidence. The twin levels of dyadic performance/risk management and the management of a portfolio of performance/risks is addressed, employing Agency Theory to guide the analysis. The empirical evidence relates to the downstream management of dealerships by a large multinational organisation. Propositions are derived from the analysis relating to the issues and mechanisms that may be employed to effectively manage a portfolio of supply chain performance and risks

Missing Links: Referrer Behavior and Job Segregation

The importance of networks in labor markets is well-known, and their job segregating effects in organizations taken as granted. Conventional wisdom attributes this segregation to the homophilous nature of contact networks, and leaves little role for organizational influences. But employee referrals are necessarily initiated within a firm by employee referrers subject to organizational policies. We build theory regarding the role of referrers in the segregating effects of network recruitment. Using mathematical and computational models, we investigate how empirically-documented referrer behaviors affect job segregation. We show that referrer behaviors can segregate jobs beyond the effects of homophilous network recruitment. Further, and contrary to past understandings, we show that referrer behaviors can also mitigate most if not all of the segregating effects of network recruitment. Although largely neglected in previous labor market network scholarship, referrers are the missing links revealing opportunities for organizations to influence the effects of network recruitment

A Design Theory for Secure Semantic E-Business Processes (SSEBP)

This dissertation develops and evaluates a Design theory. We follow the design science approach (Hevener, et al., 2004) to answer the following research question: "How can we formulate a design theory to guide the analysis and design of Secure Semantic eBusiness processes (SSeBP)?" Goals of SSeBP design theory include (i) unambiguously represent information and knowledge resources involved in eBusiness processes to solve semantic conflicts and integrate heterogeneous information systems; (ii) analyze and model business processes that include access control mechanisms to prevent unauthorized access to resources; and (iii) facilitate the coordination of eBusiness process activities-resources by modeling their dependencies. Business processes modeling techniques such as Business Process Modeling Notation (BPMN) (BPMI, 2004) and UML Activity Diagrams (OMG, 2003) lack theoretical foundations and are difficult to verify for correctness and completeness (Soffer and Wand, 2007). Current literature on secure information systems design methods are theoretically underdeveloped and consider security as a non-functional requirement and as an afterthought (Siponen et al. 2006, Mouratidis et al., 2005). SSeBP design theory is one of the first attempts at providing theoretically grounded guidance to design richer secure eBusiness processes for secure and coordinated seamless knowledge exchange among business partners in a value chain. SSeBP design theory allows for the inclusion of non-repudiation mechanisms into the analysis and design of eBusiness processes which lays the foundations for auditing and compliance with regulations such as Sarbanes-Oxley. SSeBP design theory is evaluated through a rigorous multi-method evaluation approach including descriptive, observational, and experimental evaluation. First, SSeBP design theory is validated by modeling business processes of an industry standard named Collaborative Planning, Forecasting, and Replenishment (CPFR) approach. Our model enhances CPFR by incorporating security requirements in the process model, which is critically lacking in the current CPFR technical guidelines. Secondly, we model the demand forecasting and capacity planning business processes for two large organizations to evaluate the efficacy and utility of SSeBP design theory to capture the realistic requirements and complex nuances of real inter-organizational business processes. Finally, we empirically evaluate SSeBP, against enhanced Use Cases (Siponen et al., 2006) and UML activity diagrams, for informational equivalence (Larkin and Simon, 1987) and its utility in generating situational awareness (Endsley, 1995) of the security and coordination requirements of a business process. Specific contributions of this dissertation are to develop a design theory (SSeBP) that presents a novel and holistic approach that contributes to the IS knowledge base by filling an existing research gap in the area of design of information systems to support secure and coordinated business processes. The proposed design theory provides practitioners with the meta-design and the design process, including the system components and principles to guide the analysis and design of secure eBusiness processes that are secure and coordinated

Modeling User-Affected Software Properties for Open Source Software Supply Chains

Background: Open Source Software development community relies heavily on users of the software and contributors outside of the core developers to produce top-quality software and provide long-term support. However, the relationship between a software and its contributors in terms of exactly how they are related through dependencies and how the users of a software affect many of its properties are not very well understood. Aim: My research covers a number of aspects related to answering the overarching question of modeling the software properties affected by users and the supply chain structure of software ecosystems, viz. 1) Understanding how software usage affect its perceived quality; 2) Estimating the effects of indirect usage (e.g. dependent packages) on software popularity; 3) Investigating the patch submission and issue creation patterns of external contributors; 4) Examining how the patch acceptance probability is related to the contributors\u27 characteristics. 5) A related topic, the identification of bots that commit code, aimed at improving the accuracy of these and other similar studies was also investigated. Methodology: Most of the Research Questions are addressed by studying the NPM ecosystem, with data from various sources like the World of Code, GHTorrent, and the GiHub API. Different supervised and unsupervised machine learning models, including Regression, Random Forest, Bayesian Networks, and clustering, were used to answer appropriate questions. Results: 1) Software usage affects its perceived quality even after accounting for code complexity measures. 2) The number of dependents and dependencies of a software were observed to be able to predict the change in its popularity with good accuracy. 3) Users interact (contribute issues or patches) primarily with their direct dependencies, and rarely with transitive dependencies. 4) A user\u27s earlier interaction with the repository to which they are contributing a patch, and their familiarity with related topics were important predictors impacting the chance of a pull request getting accepted. 5) Developed BIMAN, a systematic methodology for identifying bots. Conclusion: Different aspects of how users and their characteristics affect different software properties were analyzed, which should lead to a better understanding of the complex interaction between software developers and users/ contributors

Designing an agent-based model of SMEs to assess flood response strategies and resilience

In the UK, flooding is responsible for significant losses to the economy due to the impact on businesses, the vast majority of which are Small and Medium Enterprises (SMEs). Businesses of this nature tend to lack formal plans to aid their response to and recovery from disruptive events such as flooding. This paper reports on work on how an agent-based model (ABM) is being developed based on interview data gathered from SMEs at-risk of flooding and/or have direct experience of flooding. The ABM will enable simulations to be performed allowing investigations of different response strategies which SMEs may employ to lessen the impact of flooding, thus strengthening their resilience

Supply chain coordination using an adaptive distributed search strategy

A tree search strategy is said to be adaptive when it dynamically identifies which areas of the tree are likely to contain good solutions, using information that is gathered during the search process. This study shows how an adaptive approach can be used to enhance the efficiency of the coordination process of an industrial supply chain. The result is a new adaptive method (called the adaptive discrepancy search), intended for search in nonbinary trees, and that is exploitable in a distributed optimization context. For the industrial case studied (a supply chain in the forest products industry), this allowed reducing nearly half the time needed to obtain the best solution in comparison with a standard nonadaptive method. The method has also been evaluated for use with synthesized problems in order to validate the results that are obtained and to illustrate different properties of the algorith

Predicting Social Change: Transforming Victims of Child Sex Trafficking in India and the United States

Human trafficking is a huge global issue that is highly linked to issues of poverty, physical abuse, and psychological control, culminating in the buying and selling of human beings, or what we call “modern day slavery.” For my Global Honors thesis, I applied a fairly optimistic philosophical human rights theory to an unimaginable human rights issue that is taking place all over the world. This paper focuses on domestic child sex trafficking in the U.S. and India along with the unique socioeconomic, political, and cultural factors that contributes to trafficking in these countries. I found that the international community, non-profits, NGOs, and individuals are all tackling this problem from many angles in unique ways that are largely based on empathy and a concern for fairness. In this way, social change is occurring

Beauty Contests, Bubbles and Iterated Expectations in Asset Markets

In a financial market where traders are risk averse and short lived, and prices are noisy, asset prices today depend on the average expectation today of tomorrow's price. Thus (iterating this relationship) the date 1 price equals the date 1 average expectation of the date 2 average expectation of the date 3 price. This will not in general equal the date 1 average expectation of the date 3 price. We show how this failure of the law of iterated expectations for average belief can help understand the role of higher order beliefs in a fully rational asset pricing model and explain over-reaction to (noisy) public information.Beauty Contests, Bubbles and iterated expectations in Asset Markets

After Heparin: Protecting Consumers From the Risks of Substandard and Counterfeit Drugs

Based on case studies, examines globalization and quality management trends in pharmaceutical manufacturing, barriers to Federal Drug Administration oversight, and the security of pharmaceutical distribution. Makes policy recommendations to ensure safety