S. Sinan Erzurumlu

This study examines how business model innovations (BMI) generate dynamic capabilities (DCs) for organizational resilience. Drawing on the interaction of BMI as a change process and DCs perspectives, we study this question through twelve deep tech ventures facing compounding technical, market, commercial, and social uncertainties. We identify five business model design moves that deep tech ventures adopt to navigate these uncertainties. We map these five design moves to the sensing-seizing-transforming framework, showing that they generate a resilience capability stack comprising versatility, flexibility, adaptability, and collaboration. Tracing disruption episodes across our cases, we identify a mechanism we term capability repurposing where DCs generated through BMI for one function can be redirected to serve a different function when disruptions demand it. Sensing capabilities built for market detection were redirected toward market repositioning; seizing capabilities built for operational execution enabled strategic pivots; and transforming capabilities built through ecosystem governance sustained reconfiguration while ventures adapted. Critically, we identify ecosystem co-development as a necessary condition such that without it, sensing and seizing capabilities remain available but cannot be deployed for resilience. Our study extends BMI research by specifying the change process through which BMI generates DCs for resilience, and contributes to the DCs literature by operationalizing sensing-seizing-transforming at the business model level. For practitioners, we offer a diagnostic framework linking BMI patterns to specific capabilities, enabling managers to identify which design moves are present and where gaps in their resilience architecture exist.

Private companies seeking to heighten their social responsibility and reduce ecological impacts often lack practical approaches to discern high‐impact and cost‐effective changes. Deeper understanding of the interrelated economic, social, and ecological systems reflected in the United Nations Sustainable Development Goals (UN SDGs) can enhance their ability to positively connect and influence both internal and external aspects of the integrated business and socio‐ecological system. Through an inductive study of three companies, this article demonstrates that systems thinking provides a valuable approach to help companies to understand and map the systems in which they operate, enabling them to expand their sustainability practices even as they address profit‐versus‐impact conflicts. We examine how strategic business goals and activities interplay with an organization's socio‐ecological system and thereby enhance business engagement with the SDGs. Our key contribution is a systems‐minded sustainable business framework using three processes: goal–purpose alignment, partnerships, and systemic interplay. We explain each company's sustainability efforts and their relative engagement with the SDGs as well as relative impact of such engagement on the company in return.

Firms that operate in high-velocity markets must configure and utilize diverse technological innovation capabilities (TICs). TICs provide the firm with technological strength and adaptability to manage technological changes with respect to demand changes on the customer value trajectory. In this paper, we examine the configuration of a high tech firm’s TICs involving R&D, manufacturing and marketing capabilities to develop technology exploring or market exploiting activities in response to shifts in the customer value trajectory. We analyze the cases of micro, electrical, mechanical systems (MEMS) accelerometer innovators, and identify strategic configuration of TICs that has been necessary to trace the customer value trajectory with technological changes. We further show how the stability of the customer value trajectory plays a role for the firm in market transition to configure and utilize its TICs for exploring or exploiting the market. Based on our findings, we offer a managerial decision-making framework regarding strategic management of TICs with respect to the customer value trajectory in high-velocity markets.

Problem definition: Firms developing novel and innovative products regularly face a canonical product development and introduction problem: introduce a proven and immediately available product or delay product introduction until the successful development of an advanced version. Academic/practical relevance: Limited access to resources for the development of an advanced version adds another wrinkle to this problem, particularly for cash-constrained start-ups. For such start-ups, the introduction of an on-hand product can generate additional funds to support the development of an advanced product. However, the lower performance of the on-hand product can negatively impact the perception of the firm’s future products and lower future profitability. Methodology: We study the trade-off between revenues that an on-hand product generates for research and development funding and the negative effect it has on future profits. We characterize the optimal introduction timing of the on-hand product as a function of the financial resource constraints, the interdependence between these sequential products and the cost of development. Results: We identify important differences between the optimal product introduction strategies of a start-up and an established firm. Specifically, although it is always optimal for an established firm to accelerate the launch of a better-quality on-hand product, a start-up might find it optimal to delay its launch. The impact of technological failure and different forms of learning on the optimal strategy of the start-up are also explored. We translate our analytical findings into a managerial framework and illustrate these results using examples from the pharmaceutical and medical devices industries.

Problem definition: We examine how the presence of capital market frictions influences the decision to invest in production cost reduction and the resultant production volume. This investment can increase the firm’s cash flow by increasing the profit margin, but it can also decrease the firm’s risk-free cash reserves and thus affect its exposure to capital market frictions. Academic/practical relevance: Process improvement aimed at production cost reduction has generated myriad of theoretical questions about efficient investment options and capacity choices. From a managerial perspective, process improvement is a fundamental concern in operations strategy. Nevertheless, its analysis typically excludes financial constraints by assuming a perfect capital market. Methodology: We formulate a two-stage profit maximization model in which a capital-constrained firm commits to a cost-reduction investment in the first stage in anticipation of its production decision in the second stage of this two-stage decision process. The firm considers capital market frictions when making decisions at each stage, while considering uncertainty in demand for its offering and in reducing its unit production cost. Results: When a firm faces small initial capital and low preinvestment unit production costs, it can benefit from investing in production cost reduction in the presence of capital market frictions more so than in their absence. Moreover, uncertainty in the production cost reduction mitigates the impact of market frictions on the net benefit (i.e., additional profit), whereas demand uncertainty decreases the feasible parameter space, where investing in production cost reduction is optimal. Managerial implications: A firm’s decision to invest in production cost reduction affects its operational and financial capabilities. Managers should thus consider this investment as an operational hedge not only against the uncertainty of matching supply and demand but also against exposure to capital market frictions and the resultant financial risk.

High market uncertainty impedes an entrepreneur’s ability to evaluate the state of the market for a business opportunity. For many entrepreneurial ventures, data collection and analysis techniques and technologies are becoming an important source to manage uncertainty. This trend is often referred to as “data-driven entrepreneurship.” We consider a dynamic approach using data to overcome market uncertainty for business opportunity-related evaluations. In particular, we examine the entrepreneur’s investment portfolio in which each investment generates expected returns and some information about a specific aspect of the market for a single business opportunity. We develop a model that analyzes imperfect market data (e.g., financial, social, regulatory), while factoring in the entrepreneur’s risk preference and operational shortages of resources, routines, reputation, and regulations. Our numerical findings show that, rather than pursuing the highest expected returns, an entrepreneur may choose perfect information, risk hedging, or market-controlling investments based on his/her cash level and risk preference. Hence, the entrepreneur, fueled by the availability of data analysis, could overcome uncertainties and obtain better insights for business opportunity decisions.

The innovation has been recognized as a competitive advantage for almost all organizations. Yet, it has been a rather elusive topic when it comes to implementation. Operations design and strategy are mostly concerned about effective implementation of ideas. Hence, in this paper we marry these two fields (operations design and innovation), and identify three key areas for evaluating the innovation strategy, based on our previous research on innovation management. We further offer three prescriptions for practical implementation, which may be of value to managers with their assessment of the value of their innovation strategies.

This research explores a firm’s process investment decision to reduce its unit production cost in the presence of capital market frictions, prior to making a production decision. This investment depletes the firm’s risk-free assets and creates two potentially counteracting effects: an operational effect associated with unit production cost reduction and a friction effect that captures the change in financing costs when the firm has to borrow money. Based on interactions of these two effects, we find parametric conditions when investment is optimal and show that the benefit from investing in cost reductions may increase with the level of market frictions, particularly, when the firm’s initial unit cost and capital are both sufficiently low and the investment’s impact on the unit cost is sufficiently high. We further find that technology uncertainty mitigates the impact of market friction on the benefit of investing, whereas demand uncertainty increases the feasible parameter space where the investment is optimal.