Manjunath Padigar

Businesses often strive for frictionless customer experiences, assuming that customers always desire seamless interactions. However, recent academic and practitioner discussions suggest that not all forms of friction are detrimental. Reconciling the conflicting views, we propose a framework that defines friction as simply the effort customers exert to complete tasks related to their consumption goals. Furthermore, drawing from the goal striving theory and customer experience literature, we identify and propose four types of friction based on dimensions of task desirability and task value: frustrating, constructive, preference‐based, and rewarding. Our framework challenges the prevailing business practice of eliminating all friction, as evidenced by a topic modeling analysis of announcements related to achieving frictionless customer experiences. Instead, we posit that while frustration friction should be minimized, the other three types of friction offer opportunities for businesses to enhance customer value. Particularly, we caution managers that eliminating constructive friction (i.e., customer effort in low‐desirability, high‐value tasks) may hinder value creation. We also recommend that managers find opportunities to infuse rewarding and preference‐based friction to enhance customer experience. By understanding these nuances, businesses can strike a balance between friction reduction and value optimization in their customer experience designs.

Even as more companies integrate artificial intelligence (AI) into their new products and services, little research outlines the strategic implications of such AI adoption. Therefore, the present study investigates how investors respond to announcements of new product innovations integrated with AI by non-software firms (AI-NPIs), with the prediction that they respond favorably if the firms feature a marketing department with substantial power; such firms likely possess the marketing resources and assets needed to ensure the success of AI-NPIs. An event study with a sample of 341 announcements by 77 S&P 500 firms between 2009–2018 supports this prediction. Furthermore, the relationship between marketing department power and investor response intensifies when the announcement (1) occurs in later innovation stages, (2) involves the sourcing of external innovation assets, and (3) refers to more complex innovations. These findings have both theoretical and managerial implications.

In an extension of the entrepreneurship literature's long-standing emphasis on the role of human capital in attracting startup funding, we propose that tech-based startup founder’s ambidexterity and experience-based human capital have direct and interactive effects on new venture funding. Drawing on the human capital perspective, we consider ambidexterity an ability-based human capital that helps entrepreneurs navigate new venture environments and carry out entrepreneurial tasks more effectively. We compiled a unique dataset by gathering data from Crunchbase, social media sites, and entrepreneur’s online communications posted on Reddit. On the basis of text analyses on 115 startup founder’s public discourse using a purpose-built dictionary to measure ambidexterity, our empirical results confirm that founder ambidexterity has positive effects on tech startup funding and that these effects are moderated by founder’s experience-based human capital in terms of prior career experience and startup creation experience. This finding is complemented by semistructured interviews with venture capitalists providing evidence that funders consider founder ambidexterity in their investment decisions. Implications for literature and practice are discussed.