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Recent Journal Publications by COB Faculty

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Academic Journal
Finance

“Board members' influence on resource investments to start-ups and IPO outcomes: Does prior affiliation matter?”

Using data that contains career paths of start-up board members, we examine how their prior affiliations with various types of venture capital (VC) firms promote financial and human resource investments from the affiliated VC firm. We find that the likelihood of affiliation-based resource investments such as financing and board member engagement depends on the type of VC firms (e.g., bank-affiliated, corporate). Meanwhile, we find little evidence that affiliation-based resource investments lead to lower IPO costs and better post-IPO performances (i.e., return on assets, buy-and-hold abnormal returns, and failure rate). While prior affiliation could improve the inflow of resources, it might worsen screening and monitoring activities.
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Academic Journal
DSGN - Apparel Design

“Body-product relationship for aging women examined through the lens of functional anthropometry”

The purpose of this research was to understand how measurements of the aging body change in the seated and standing positions. An integrated approach was taken to select the appropriate 3D scanning technology, develop a landmarking method, and position the body to analyze the waist–hip–thigh region. Each part of the method was developed to enable an in-depth analysis of circumference measurements and shape change, including the expansion and contraction of body shape across different postures. New 3D scanning methods to quantify diverse bodies can improve product fit and create inclusive, quality design for all.
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Academic Journal
Supply Chain

“Building a More Complete Theory of Sustainable Supply Chain Management Using Case Studies of Ten Exemplars”

Case studies of 10 exemplar firms are used to build a coherent and testable model of the elements necessary to create a sustainable supply chain. The cases build on previous research by examining the chain as an entirety, by explicitly examining both the social and environmental outcomes of the chain's activities, and by explicitly asking what these exemplar organizations are doing that is unique in regards to managing their supply chains in a sustainable manner. The analysis suggests that the practices that lead to a more sustainable supply chain are equal parts best practices in traditional supply chain management and new behaviors, some of which run counter to existing accepted “best” practice.
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Academic Journal
Finance

“Business Cultural Intelligence Quotient: A Five-Country Study”

Cultural intelligence (CI) has often been linked to performance at the individual, team and firm levels as a key factor in international business success. Using a new measure of CI, the business cultural intelligence quotient (BCIQ), our study provides empirical evidence on several key antecedents of CI using data onbusiness professionals across five diverse countries (Austria, Colombia, Greece, Spain and USA). The findings suggest that the most important factors leading to cultural intelligence, in order of importance, are: the number of countries that business practitioners have lived in for more than six months, their level of education and the number of languages spoken. We find that cultural intelligence varies across countries, suggesting that some countries have a higher propensity for cross-cultural business interactions. By teasing out the common antecedents of BCIQ among professionals, our findings may help with screening and training professionals for international assignments. Future research may examine the environmental (country-specific) factors associated with a higher propensity for cultural intelligence (such as immigration, cultural diversity, languages spoken, and international trade) to explain the effect of country of origin on cultural intelligence in the professional community.
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Academic Journal
Business Analytics

“Business Performance Prediction in Location-based Social Commerce”

Social commerce and location-based services provide a data platform for coexisting and competing businesses in geographical neighborhoods. Our research is aimed at mining data from such platforms to gain valuable insights for better support to strategic and operational business decisions. We develop a computational framework for predicting business performance that takes into account both intrinsic (e.g., attributes) and extrinsic (e.g., competitions) factors. Our experiments on synthetic and real datasets demonstrated superiority of a hybrid prediction model that adopts both link-based and context-based assumptions.
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