Due to the sophistication of cyber threats, organizations need to be defended on a strategic level, leading to the emergence of the cybersecurity leader role. However, the necessary competencies required for successful response are not fully understood due to the unique demands of the role. To bridge this gap, it is crucial to explore how these competencies manifest in practice. Data were collected through interviews and open ended surveys of cybersecurity leaders, which were analyzed using the method of thematic analysis. Four key themes related to necessary competencies were identified: one on knowledge, two on skills, and one on attitudes. The study found that cybersecurity leaders emphasize the importance of having knowledge about the organizational architecture, skills to simplify incident handling procedures, and the ability to convince management to invest in better incident preparedness. They also highlighted the need for a supportive and approachable environment to facilitate optimal cybersecurity incident handling.

CSR approach is getting noticed by more and more scholars and practitioners to assist MNC subsidiaries¡¦ performance and survival. Prahalad (2004) argued MNCs need to be able to explore and exploit opportunities from undeveloped or developing countries in pursuit of their continuous profitability and sustainability. However, how MNC subsidiaries can be organized to approach and discover the local people and social needs from emerging economies is still a question to be answered. Porter & Kramer (2002) proposed strategic CSR approach for firms to getting into sustainability. By all means of strategic CSR, firms truly realize sustainability that simultaneously obtaining economic, social and environmental performance when the CSR activities are practiced from inside out that involves the whole organization, structure, and system, and meanwhile links with firm strategies. This research adopted system perspective incorporating RBV and stakeholder perspective to systematically examine how internal CSR-related processes interact to influence MNC subsidiaries¡¦ sustainability in host country. We accordingly looked into the CSR practices and the related management processes implemented by XI MNC subsidiaries in China and Taiwan through case interviews. We identified that CSR international coordination mechanism, HRM, and TMT leadership are all important processes through which MNC subsidiaries reach sustainability in host countries by CSR practices. Besides, we found that a strong corporate social culture within subsidiaries built up through the abovementioned processes is an important factor that leads to subsidiaries¡¦ sustainability. In addition, we identified stakeholder relational capital derived from these CSR-related processes is another critical, firm-specific resource to facilitate MNC subsidiaries¡¦ sustainable performance. On the whole, the findings upon the case studies of our research proposed a systematic MNC subsidiaries CSR framework that explains how, why, and under which influential factors CSR practices are implemented. This research therefore can contribute to the theoretical developments in CSR theories, RBV, and international management theories as well as firms¡¦ management practices in conducting CSR for sustainability.

Designers do not merely develop concepts; they are increasingly involved in testing product concepts and learning consumer preference. However, designers’ decision making processes in these tasks have been little studied. In the two essays, I apply decision making frameworks to concept testing and preference learning to study consumer’s and designer’s biases. In my first essay, I study consumer bias in concept testing. When consumers test new products, they are often asked to choose which product they prefer. However, a choice question can elicit biased preference because consumers simply choose the product that is superior on the attribute serving their purchase purpose. My studies show that when consumers are asked to predict which product they will enjoy more, they are more likely to prefer the product that actually reflects their consumption utility. These findings suggest that making trade-offs is avoided in the choice question, but is encouraged in the enjoyment prediction question. Thus, a simple change of question format, in otherwise identical product comparisons, elicits different answers. This holds true when product attributes are easy to evaluate; when product attributes are hard to evaluate, changing question format does not affect consumer choice. My second essay examines designer bias in preference learning. When designers predict consumer preference for a product, they often base their predictions on consumer preference for similar products. However, this categorization-based strategy can result in biased predictions because categorical similarity is not diagnostic for preference prediction. I conducted two studies by applying a Multiple Cue Probability Learning experiment to a designer’s prediction task. I found that when subjects used a sequential learning strategy, making a sequence of predictions and receiving feedback, they increased prediction accuracy by 14% on average. When they made predictions with multiple sets, with a break between each set during which they reflected on what they had learned, their prediction accuracy further improved by 7% on average. In sum, I demonstrate bias and propose approaches to avoid them in two design tasks. My two essays show that the decision making frameworks are crucial in understanding and improving the successful outcome of the design process.

Designers do not merely develop concepts; they are increasingly involved in testing product concepts and learning consumer preference. However, designers’ decision making processes in these tasks have been little studied. In the two essays, I apply decision making frameworks to concept testing and preference learning to study consumer’s and designer’s biases. In my first essay, I study consumer bias in concept testing. When consumers test new products, they are often asked to choose which product they prefer. However, a choice question can elicit biased preference because consumers simply choose the product that is superior on the attribute serving their purchase purpose. My studies show that when consumers are asked to predict which product they will enjoy more, they are more likely to prefer the product that actually reflects their consumption utility. These findings suggest that making trade-offs is avoided in the choice question, but is encouraged in the enjoyment prediction question. Thus, a simple change of question format, in otherwise identical product comparisons, elicits different answers. This holds true when product attributes are easy to evaluate; when product attributes are hard to evaluate, changing question format does not affect consumer choice. My second essay examines designer bias in preference learning. When designers predict consumer preference for a product, they often base their predictions on consumer preference for similar products. However, this categorization-based strategy can result in biased predictions because categorical similarity is not diagnostic for preference prediction. I conducted two studies by applying a Multiple Cue Probability Learning experiment to a designer’s prediction task. I found that when subjects used a sequential learning strategy, making a sequence of predictions and receiving feedback, they increased prediction accuracy by 14% on average. When they made predictions with multiple sets, with a break between each set during which they reflected on what they had learned, their prediction accuracy further improved by 7% on average. In sum, I demonstrate bias and propose approaches to avoid them in two design tasks. My two essays show that the decision making frameworks are crucial in understanding and improving the successful outcome of the design process.