Fitness technology feature use items were not available in the literature, and thus, were developed for the current study. Items were developed for each feature set following the procedure described next. We used a four-step process to determine the fitness technology features that make up our first-order subconstructs. First, we compiled a list of currently available fitness devices and their associated apps using lists of wearables published in popular media outlets. The original list contained 72 devices and was compiled using lists of wearables from CNET, PC Magazine, The Wall Street Journal, Engadget, Gizmodo, and others. While not comprehensive, the redundancy across multiple lists suggests that our list, at the very least, contains the most popular devices in the wearables category at the time the data was collected. Second, the three researchers independently visited every website of each device/app on the list and collected the features the company advertised for the fitness technology. Third, all three of the researchers' feature lists were compared, discussed, and used to create an integrated list. Fourth, once survey items were created, an expert panel was convened to examine the feature list and scales as described below.Accepted procedural methods (Churchill 1979;MacKenzie et al. 2011) were followed in developing the fitness technology use items. Once the items were developed, an expert panel was convened. The expert panel consisted of two faculty members who are well versed in surveybased methodologies, two faculty members who were active users of fitness technologies, and two employees of a fitness technology company. The expert panel was instructed to examine the entire survey instrument for clarity and to provide feedback on wording and note if any fitness technology features were missing. The expert panel did not provide any new fitness technology features, which indicated our list was reasonably comprehensive. The expert panel did suggest wording changes to the fitness technology features set use items and the addition of a few more fitness device and apps to our list (primarily new versions of devices already present in our list). We compiled the expert panel wording suggestions and considered each suggestion. Most wording suggestions from the expert panel were implemented, improving the clarity of the survey items.

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Purpose -The purpose of the paper is to provide a conceptual foundation to enhance the body of knowledge related to supplier selection in light of global supply chain disruptions and risk. Design/methodology/approach -The proposed tool is based on a multi-criteria optimization framework, which will enable the user to gain a better understanding of how the consideration of each of these risk measures will affect the recommended solution/supply base. The model serves as a complement to existing supplier selection models by incorporating regional risks associated with potential suppliers' locations and density risks based on great circle distance measures. Findings -The paper demonstrated the proposed model by using the great circle distance measure to calculate the density risk and two secondary data sources to capture environmental risk. One measure captures a variety of environmental issues such as political, legal, security, fiscal, labor, and regulatory issues. The other measure captures the historical effects of weather on dollar and human losses in each country of the world, which represents the potential for severe weather events and the country's ability to react to these events. Research limitations/implications -Although the paper does not consider all possible risks, it augments prior research through the development of a decision support tool that offers supply risk mitigation when sourcing globally. Specifically, the tool allows for the analysis and mitigation of two key global risk measures, environmental risk and density risk, when selecting suppliers for mission-critical parts. The model is able to support various sourcing strategies such as sole, multiple and cross sourcing and can be used in conjunction with other disruption mitigation strategies such as supply redundancy. Practical implications -Global sourcing has provided significant performance enhancements, but has put firms in a vulnerable position relative to the potential devastating effects of supply disruptions. While supply managers are cognizant of the risks associated with global sourcing, limited knowledge and tools are available to allow them to mitigate these risks. Although it would need to be adapted to the nuances of company supply chains, it is believed that the tool provides value to managerial decision making relative to the sourcing of mission critical parts/products. Originality/value -Prior work in this area has not adequately incorporated contemporary issues and risks in global sourcing. The paper augments prior research through the development of a multi-objective decision support model for strategic supplier selection that is focused on two important contemporary factors: environmental risk and density risk. The proposed model captures important interdependent relationships between these two factors that have not been considered in prior selection models.

Fitness technologies are a prominent example of the societal trend towards personal informatics. These technologies pair devices that have various embedded sensors with one or more apps to allow for the collection, analysis, socialization, and management of individuals' health and wellness data. We have limited insight into what drives the use of fitness technologies or how they may contribute to wellness outcomes. To address this gap, our study examines how exercise goals are related to fitness technology feature set use and how the use is associated with a measure of the exercisers' psychological well-being (ie, subjective vitality).We find that intrinsic exercise goals (eg, enjoyment or competence) are associated with the use of features that allow users to collect, analyse, and inform their exercise progress.Body-focused extrinsic exercise goals (eg, appearance) are also associated with the use of such features but are nega-

Supply chain practices often put companies and their supply chains at risk. One of the most serious risks is disruptions. While many types of disruptions have been considered, little attention has been given to disruptions caused by information technology (IT) security incidents. Partner cooperation can assist in preventing or mitigating damage from IT security breaches in supply chains, where breaches can disrupt production, cause loss of essential data, and compromise confidential information. We develop a generalizable mathematical model that quantifies IT security risk in the supply chain. We then show how to find solutions for optimal risk reduction under several definitions of optimality: minimizing upstream risk, minimizing downstream risk, and minimizing global (supply chain) risk. We show how to develop curves for each of the above scenarios that indicate when extra funds should be spent on security, which security controls should be implemented, and when subsidies among partners are beneficial.