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Knowledge‐intensive firms are growing in importance yet there are few tools to help managers to analyze and improve their performance, which this paper aims to describe.

This paper builds on Michael Porter's strategic frameworks for industrial firms. It outlines how his frameworks, in particular the five forces and value chain, need to be modified if they are to be effectively applied to knowledge‐intensive firms.

Managers of knowledge‐intensive firms need to use the old tools in new ways, if they are to improve their business models and ultimately increase their profitability.

The paper outlines ways for managers of knowledge‐intensive firms to improve their firm's performance. First, managers using a revised five forces can improve their value capture by reducing bargaining power of its experts, making outsourcing of expert services more attractive, or improving their reputational status. Second, the paper outlines a continuum of business models and suggests that the appropriate choice of business model depends on the firm's problem‐solving expertise, its target clients, desired risk level and aspirations. The paper elaborates on the business model by examining choices surrounding the scope of the firm's problem‐solving activities, suggesting that these allow the firm to find profitable niches.

This is one of the first attempts to develop strategic tools that managers of knowledge‐intensive firms can used to increase their firm's profitability.

This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not.

This study is based on an event study using data from two stock markets in China.

The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along.

This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets.

Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.

The primary purpose of this chapter is to offer a conceptual/theoretical understanding of post-M&A integration rationales and/or actions which pose a challenge to acquired firm customers in acquisitions of knowledge-intensive firms, and thus trigger M&A value destruction. The approach takes the form of a literature overview and conceptual development. As a step toward developing a more elaborate understanding of a customer-centered perspective, this conceptual study identifies five key factors that may lead to value leakage/destruction for acquirers’ of knowledge-intensive firms. Specifically, it identifies acquisition motive, specific acquired firm employees other than the engineers and scientists, size of the acquired firm customer-base, M&A customer compatibility, and the acquirer’s own customers’ behavior as integration rationales and/or actions which pose a challenge to acquired firm customers. In addition, the chapter offers a theoretical framework that serves as an analytical tool, and can thus be used as a foundation for future empirical work on analyzing acquirers’ destruction of value in knowledge-intensive acquisitions through the neglect of acquired firm’s customers. This study does not claim to have provided exhaustive list of all factors regarding acquirer’s integration rationales and/or actions that influence acquired firm customers. Nonetheless, for researchers seeking to build a more comprehensive framework relating to the impact of acquirer’s integration rationales and/or actions on acquired firm’s customers, this framework may serve as a solid foundation for achieving that goal. For practitioners, this study points to the importance of knowledge held by acquired firm customers and the need to maintain such customer relationships in order to avert acquirer’s post-M&A value destruction. In addition, acquirers may also recognize that post-M&A integration changes required following M&A should not be restricted to only the firm’s internal activities and resource deployment but should extend to how the firm interacts or relates with other external value creation actors. This chapter contributes by highlighting and stimulating a discussion on the important role of acquired firm customers in acquisitions of knowledge-intensive firms in informing our understanding of the sources of M&A value leakage/destruction.

Israel, characterized by various knowledge-intensive entrepreneurial firms, provides an interesting case study for examining sector-based differences and “small country” regional patterns. This chapter has a dual goal of exploring sector and regional differences of knowledge-intensive firms in Israel. The first goal is to depict similarities and differences between firms in three knowledge-intensive sectors: Life Sciences, information technology, and Cleantech. The second goal questions whether the geographical distribution of these firms across regions is associated with different levels of knowledge concentration and organizational homogeneity. Regional and sector-based differences were measured by firm-level network structures, funding patterns, and innovation proxies. One way analysis of variance tests were conducted for attaining these research goals. The main findings show that while most regions exhibit similar patterns of firm and network characteristics, many differences exist on the sector level that are associated with sector-specific attributes. These findings support the notion of a “small country inter-regional homogeneity effect.”

This chapter investigates how regional start-up rates in the knowledge-intensive services and high-tech industries are influenced by knowledge spillovers from both universities and firm-based R&D activities. Integrating insights from economic geography and organizational ecology into the literature on entrepreneurship, we develop a theoretical framework which captures how both supply- and demand-side factors mold the regional bedrock for start-ups in knowledge-intensive industries. Using multilevel data of all knowledge-intensive start-ups across 286 Swedish municipalities between 1994 and 2002 we demonstrate how characteristics of the economic and political milieu within each region influence the ratio of firm births. We find that knowledge spillovers from universities and firm-based R&D strongly affect the start-up rates for both high-tech firms and knowledge-intensive services firms. Further, the start-up rate of knowledge-intensive service firms is tied more strongly to the supply of university educated individuals and the political regulatory regime within the municipality than start-ups in high-tech industries. This suggests that knowledge-intensive service-start-ups are more susceptible to both demand-side and supply-side context than is the case for high-tech start-ups in general. Our study contributes to the growing stream of research that explains entrepreneurial activity as shaped by contextual factors, most notably academic institutions, such as universities that contribute to knowledge-intensive start-ups.

This paper aims to present findings on outsourcing practices in small service firms in Iceland, where the prime focus is on knowledge-intensive service firms.

To gain information on the scope and reason for outsourcing, telephone and online surveys were used. In total, 802 firms participated in the surveys, which were conducted in the period 2009-2018.

The results show that knowledge-intensive firms outsource far more than other service firms and are also more likely to have an outsourcing strategy. The grounds for increased outsourcing are cost reduction and strategic reasons, such as a focus on core competency and the search for external knowledge. In comparison with other firms, knowledge-intensive firms are increasingly outsourcing cleaning, security services, canteen and transportation, IT processes, human resource management, training and consulting. Additionally, managers of these firms select suppliers more on the basis of cost and quality. They also realize more cost savings as a consequence of outsourcing. Outsourcing had a very limited effect on employment in the firms, while cost reduction was achieved in 48.3 per cent of the firms involved.

The findings are in line with the resource-based theory and, interestingly, this is not limited to knowledge-based firms, but to a large portion of service firms as well.

This is the first in-depth study on outsourcing patterns in knowledge-intensive firms, which uses theoretical classification in empirical analysis.

Most, if not all, management control tools were formulated for firms employing an industrial value creation logic (i.e., Ford, McDonald’s, and Wal‐Mart). We argue that given the growth, both in number and importance, of firms employing a knowledge value creation logic (i.e., Accenture, Goldman Sachs, and Clifford Chance) and firms employing a network logic (i.e., Verizon, eBay, and Expedia) that these control tools should be revisited in light of this potentially critical contingency. This paper outlines the key characteristics of knowledge intensive firms and network service firms and then examines how these contingencies impact Simons’ (1995) Levers of Control and Kaplan and Norton’s (1996) Balanced Scorecard. We find that whilst each lever/perspective is still relevant for each value creation logic, the relative importance and thus intensity of use should vary between logics.

The purpose of this paper is to draw attention to the significant lower completion rate of mergers and acquisitions (M&As) by firms from emerging economies (EEs) (China in particular) compared with firms from advanced economies, and identify the country- and industry-level factors that affect the completion of cross-border M&As by Chinese firms.

This study explores the effects of economic, cultural and institutional distances and target firms in technology- and knowledge-intensive industries on the completion of cross-border M&As by Chinese firms. It also examines the interplay between distance factors and technology- and knowledge-intensive industries on cross-border M&A completion. This study adopts a quantitative approach and is based on a sample of 768 announced cross-border M&A deals by firms in China between 2000 and 2015.

The results indicate that economic distance increases the likelihood of the completion of cross-border M&As when the target is in a more developed economy than China, but decreases when the target is in a less developed economy. Cultural and institutional distances have a significant, negative impact on the completion of cross-border M&As. In addition, target technology-intensive industries have a significant direct negative effect on cross-border M&A completion and moderate the relationship between the distance factors and the likelihood of cross-border M&A completion.

The results reveal factors that affect the completion of cross-border M&As by emerging market firms (EMFs). Further research, however, is needed to discover how distance factors affect how EMFs find, evaluate and negotiate international bids. To broaden the scope of the research, data for firms from other EEs would also be required.

The study expands the literature that considers the effects of major distances on cross-border M&A completion. In addition, the importance of defining and measuring distances in the context of cross-border M&As is highlighted. Finally, the study expands knowledge on how cross-border M&As affect the internationalization strategies of EMFs by conceptualizing and testing how target industries affect cross-border M&A completion.

The global strategies of high-tech start-ups fall into two types. One is characteristic of knowledge-based firms; the other is characteristic of knowledge-intensive firms. We present two propositions related to timing of globalization and resource acquisition for each type and examine four case studies from the region around Cambridge University in the United Kingdom.

Knowledge-based start-ups target global markets from the very beginning, aiming at rapid market penetration. From the start they are highly globalized in acquiring core technology and financial and human resources.

In contrast, knowledge-intensive start-ups start in local markets and initially restrict acquisition of core technology and financial and human resources to those markets. Only at a later stage, when the local business is solidly established, do they gradually expand their businesses to global markets.

The purpose of this paper is to examine the role of geographic location of research-intensive firms in the ability to generate new research and products, which consequently affects firm value.

The authors conduct the empirical study following a three-step process. First, if pharmaceutical firms are more likely to cite the patents of other firms and other innovators that are nearby, as opposed to firms and other innovators that are far away, then location (i.e. close proximity) is likely important when it comes to the ability to learn and to use the knowledge being generated by other innovators. The authors employ a “geographic information systems” (GIS) and geo-code each pair of citing and cited patents. In addition, the authors utilize spatial statistics such as Moran’s I to analyze the spatial clustering pattern of patent citations and knowledge flows. Next, the authors measure the pharmaceutical companies’ ability to generate useful patents as a function of the amount of innovation and industrial activity that is occurring close to them. Finally, the authors test whether a firm’s location relates to its firm value. Specifically, the authors model firm value as a function of its patents quality, but the authors also allow the firm’s patents quality to be a function of its location and locational attributes. In this way, the authors establish a link between location and firm value. Using a simultaneous system of equations, the authors find that location explains patent quality, which, in turn, explains firm value. In other words, there is a positive relationship between firm value, innovation and location.

In empirical tests using pharmaceutical firms and their patents, the authors first find that firms more often cite patents of other firms that are geographically closer to them than those firms that are farther away. The authors then find that a patent’s quality is a function of the firm’s near proximity to other knowledge-intensive institutions and activities. Finally, the authors find that because patent quality is a function of a firm’s geographic location, location consequently affects firm value.

For knowledge-intensive firms, geographic location matters. More specifically, the authors contend that research-intensive firms are better able to use and to expand on existing knowledge when they are closer to other research-intensive enterprises. The implication is that firm value maximization involves a location factor.

The practical implication for investors is that investors should invest in those firms that are situated in a location that is rich in geographic innovation resources because those firms are more likely to generate more and higher quality patents or innovations.

The study is the first to establish the linkage among spatial knowledge diffusion, geographic drivers of innovation, and market valuation of the firm. The study is unique in that the authors not only present evidence on spatial knowledge flows by geo-coding the exact longitude and latitude location coordinates of citing and cited patens, but more importantly, the authors also identify geographic drivers of innovation, and examine their impacts on citation-weighted patent counts and knowledge stock. Finally, using a series of simultaneous equations, the authors show how geographic innovation resources positively affect citation-weighted patent stock and knowledge stock and consequently affect market value of the firm. Thus, the novel approach contributes not only to the literature that measures geographic localization of knowledge flow using patent citations, but also to the literature that examines the impact of geographic sources of innovations on patent outputs and patent quality and, thus on firm value for research-intensive firms.