How do markets evolve? Why are some innovations picked up straightaway whilst others take years to be commercialized? Are there first-mover advantages? Why do we behave with 'irrational exuberance' ...in the early evolution of markets as was the case with the dot.com boom? Paul Geroski is a leading economist who has taught economics to business school students, managers, and executives at the London Business School. In this book he explains in a refreshingly clear style how markets develop. In particular he stresses how the early evolution of markets can significantly shape their later development and structure. His purpose is to show how a good grasp of economics can improve managers' business and investment decisions. Whilst using the development of the Internet as a case in point, Geroski also refers to other sectors and products, for example cars, television, mobile phones, and personal computers. This short book is an ideal introduction for managers, MBA students, and the general reader wanting to understand how markets evolve. Available in OSO: http://www.oxfordscholarship.com/oso/public/content/economicsfinance/0199248893/toc.html
There are numerous biological and small‐molecule therapies currently under investigation for the prevention and treatment of COVID‐19. This article focuses on antibody therapies that target the virus ...itself, including convalescent plasma and monoclonal antibodies against SARS‐CoV‐2, and discusses their efficacy in clinical trials and likely future role.
Task-Dependent Algorithm Aversion Castelo, Noah; Bos, Maarten W.; Lehmann, Donald R.
Journal of marketing research,
10/2019, Volume:
56, Issue:
5
Journal Article
Peer reviewed
Research suggests that consumers are averse to relying on algorithms to perform tasks that are typically done by humans, despite the fact that algorithms often perform better. The authors explore ...when and why this is true in a wide variety of domains. They find that algorithms are trusted and relied on less for tasks that seem subjective (vs. objective) in nature. However, they show that perceived task objectivity is malleable and that increasing a task's perceived objectivity increases trust in and use of algorithms for that task. Consumers mistakenly believe that algorithms lack the abilities required to perform subjective tasks. Increasing algorithms' perceived affective human-likeness is therefore effective at increasing the use of algorithms for subjective tasks. These findings are supported by the results of four online lab studies with over 1,400 participants and two online field studies with over 56,000 participants. The results provide insights into when and why consumers are likely to use algorithms and how marketers can increase their use when they outperform humans.
Few observers are unimpressed by the economic ambition of China or by the nation's remarkable rate of growth. But what does the future hold? This meticulously researched book closely examines the ...strengths and weaknesses of the Chinese economic system to discover where the nation may be headed and what the Chinese experience reveals about emerging market economies. The authors find that contrary to popular belief, cutting edge innovation is not a prerequisite for sustained economic vitality-and that China is a perfect case in point.
Although there are opposing theoretical arguments on the relationship between the strength of a country's employment protection laws (EPLs) and innovation, empirical evidence tilts towards a positive ...relationship. However, research has mainly focused on the early stages of the innovation process, such as R&D and patenting. This study examines the role of EPLs in the later stages of the innovation process: the commercialization of new products. In particular, we focus on EPLs' relationship with two different new product commercialization outcomes: the launch and subsequent sales of new products. Using data on small European firms, we find that, controlling for invention, stricter EPLs are negatively associated with firms' likelihood of launching new products, but positively associated with the sales from new products. We discuss the implications of our results for theory and practice.
•Past research mainly focuses on employment protection laws (EPLs) and invention.•Focus on EPLs and two aspects of new product commercialization: launch and sales.•EPLs relate negatively to new product launch decisions.•However, EPLs relate positively to new product sales.•The results hold when controlling for, and are independent of, R&D intensity.
A chemistry professor explains the mechanism of the copper(I)‐catalyzed alkyne–azide cycloaddition (CuAAC) while suggesting that by interrupting the click reaction, it is possible to exploit the ...reactivity of the copper metallacycle intermediate to synthesize new products. The students who are listening are imagining novel synthetic pathways and finding ways to access products that are typically hard to obtain. More information can be found in the Review by M. Giustiniano, G. C. Tron and co‐workers (DOI: 10.1002/chem.202303844).
Research on growth of innovations introduced to the market has gradually shifted its focus from aggregate-level diffusion to exploring how growth is influenced by a given social network structure's ...characteristics. In this paper, we critically review this branch of literature. We argue that the growth of an innovation in a social network is shaped by the network's structure. Borrowing from the field of industrial organization in economics, which defines itself as the study of the effect of market structure on market performance, we describe this new wave of research on growth of innovations as the effect of social network structure on innovation performance. Hence, social network structural characteristics should be incorporated into research on new product growth as well as into managerial marketing decisions such as targeting and new product seeding.
We review how social network structure influences innovations' market performance. Specifically, we discuss (1) a networks' global characteristics, namely average degree, degree distribution, clustering, and degree assortativity; (2) dyadic characteristics, or the relationships between pairs of network members, namely tie strength and embeddedness; (3) intrinsic individual characteristics, namely opinion leadership and susceptibility; and (4) location-based individual characteristics, namely the degree centrality, closeness centrality, and betweenness centrality of an individual network member.
Overall, we find that growth is particularly effective in networks that demonstrate the “3 Cs”: cohesion (strong mutual influence among its members), connectedness (high number of ties), and conciseness (low redundancy). We identify gaps in current knowledge, discuss the implications on managerial decision making, and suggest topics for future research.
Our objective in this paper is to measure the impact (valence, volume, and variance) of national online user reviews on designated market area (DMA)-level local geographic box office performance of ...movies. We account for three complications with analyses that use national-level aggregate box office data: (i) aggregation across heterogeneous markets (spatial aggregation), (ii) serial correlation as a result of sequential release of movies (endogenous rollout), and (iii) serial correlation as a result of other unobserved components that could affect inferences regarding the impact of user reviews. We use daily box office ticket sales data for 148 movies released in the United States during a 16-month period (out of the 874 movies released) along with user review data from the Yahoo! Movies website. The analysis also controls for other possible box office drivers. Our identification strategy rests on our ability to identify plausible instruments for user ratings by exploiting the sequential release of movies across markets-because user reviews can only come from markets where the movie has previously been released, exogenous variables from previous markets would be appropriate instruments in subsequent markets.
In contrast with previous studies that have found that the main driver of box office performance is the volume of reviews, we find that it is the valence that seems to matter and not the volume. Furthermore, ignoring the endogenous rollout decision does not seem to have a big impact on the results from our DMA-level analysis. When we carry out our analysis with aggregated national data, we obtain the same results as those from previous studies, i.e., that volume matters but not the valence. Using various market-level controls in the national data model, we attempt to identify the source of this difference.
By conducting our empirical analysis at the DMA level and accounting for prerelease advertising, we can classify DMAs based on their responsiveness to firm-initiated marketing effort (advertising) and consumer-generated marketing (online word of mouth). A unique feature of our study is that it allows marketing managers to assess a DMA's responsiveness along these two dimensions. The substantive insights can help studios and distributors evaluate their future product rollout strategies. Although our empirical analysis is conducted using motion picture industry data, our approach to addressing the endogeneity of reviews is generalizable to other industry settings where products are sequentially rolled out.
In the first decade of the 21st century product development in networks was predicted to be of ever-increasing importance to businesses of all sizes because of changes in markets, in technology, in ...networks, and in the competences of Businesses. The growth in new products’ share of businesses’ total turnover and earnings were increasing at an unprecedented speed. The entrepreneurial innovations and technological improvements had resulted in the increasingly fast development of new products and services. Businesses and industries in different countries became increasingly more linked and interdependent in networks with respect to materials, business operations and particularly product development to match the wants and needs of the global market environment to high speed product development. Businesses were therefore encountering increasingly dynamic market fragmentation, shrinking time in market, increasing product variety, demands of production to customer specifications, reduced product lifetimes, and globalization of production.Networks were vital because the competition is not business against business, but network against network. Networks are vital because an increasing part of product development was carried out in all types of networks containing physical, ICT, dynamic, and virtual networks. Speed and pressure on time in product development seemed to continue to increase because customer demands for new products seemed to continue to increase. However, a Business seldom possessed all needed competences, and managers saw product development based on networks as an important solution to meet the strong competition of the future global markets and the strong demand for innovation and innovativeness. The evolution of market demands and focus (required) on competencies of businesses could be characterized as a development from a focus on efficiency, to a focus on quality and flexibility, to a focus on speed and innovativeness.This was why it was interesting and important to research and discuss product development and especially to understand high speed product development of individualized products in fragile market segments. Consequently, findings and learning on aspects like enablers, management tools, technological tools, product development models, product development processes and network tools to speed new product development are presented in this book.
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