Влияние взаимодействия с клиентами на инновационную активность компаний сектора интеллектуальных услуг тема диссертации и автореферата по ВАК РФ 08.00.05, кандидат наук Чичканов Николай Юрьевич

• Чичканов Николай Юрьевич
• кандидат наук
• 2021

Оглавление диссертации кандидат наук Чичканов Николай Юрьевич

TABLE OF CONTENTS

INTRODUCTION

CONCLUSIONS

REFERENCES

Appendix A. Article 1 «Knowledge Intensive Business Services: Ambiguities and Continuities»

Appendix B. Article 2 «Drivers for innovation in KIBS: evidence from Russia»

Appendix C. Article 3 «The role of client knowledge absorptive capacity for innovation in KIBS»

Введение диссертации (часть автореферата) на тему «Влияние взаимодействия с клиентами на инновационную активность компаний сектора интеллектуальных услуг»

INTRODUCTION

Motivation & Research Gap. Nowadays in both developed and emerging economies the lion's share of the value added and employment is contributed by the service industries, whose rapid growth has been fueled by the rise of knowledge-intensive business services [Di Berardino, Onesti, 2020; Hidalgo, Herrera, 2020]. For instance, while the share of the service industries in GDP of the USA, EU and Japan grew about 5-10% over 1996-2007, the increase of the knowledge-intensive business services' share was about 30-40% and their contribution to the growth of GDP reached 1728% [European Competitiveness Report, 2011]. Moreover, the increase of the relevance and contribution of knowledge-intensive business services in terms of both value added1 and service export2 is also observed at emerging markets.

The term 'knowledge-intensive business services' or KIBS was introduced in the mid-1990s to describe private firms providing knowledge-intensive services required for business processes of other companies, non-commercial organizations and public entities3 [Miles et al., 1995]. Traditionally, the researchers [e.g. Muller, Doloreux, 2009; Schnabl, Zenker, 2013] classify as KIBS those firms whose main activities are devoted to accounting, auditing, management and information technology (IT) consulting, architecture, engineering, advertising as well as legal, IT-related (including computer programming), R&D, and marketing services.

In early studies KIBS were primarily considered as innovation intermediaries, complementing or replacing universities and research centers as sources of innovation knowledge, and acting as facilitators, initiators or carriers of innovation for their clients [Bilderbeek, den Hertog, 1998; den Hertog, 2000]. Later, with the development of innovation statistics, it was revealed that KIBS companies are also highly innovative themselves and are even more innovative than most other service and manufacturing industries [Gotsch et al., 2011; Hipp et al., 2015]. As a result, a new dualistic approach to the analysis of KIBS was developed which highlights that these companies can be simultaneously both intermediaries that promote the growth of innovative activity of their clients and innovators who create innovative products and services and introduce innovative solutions in their own business processes [Shearmur, Doloreux, 2019]. The main focus of the researchers has also shifted from studying the intermediary aspect of KIBS companies to the exploration of their own knowledge and innovation management practices [Scarso, 2015; J-Figueiredo et al., 2017].

1 In 2001-2016 CAGR of value added in KIBS among Silk Road countries (also taking into consideration the low base effect) was 16.6% in China, 15.7% in India, 10.1% in Russia, 13.5% in Turkey and 10.3% in Iran compared to 4.7% in the USA and 4.5% in the EU [Chichkanov et al., 2021].

2 In 2000-2013 the highest levels of the average annual growth of KIBS export were observed in transitions economies (18.7%), that were significantly ahead of both developing (12.8%) and developed (10.3%) countries [Wyszkowska-Kuna, 2016].

3 Taking into consideration this b2b nature of KIBS in this research terms 'clients' and 'customers' are used as equivalents.

One of the key features of KIBS is the application of the problem-solving project-based approach for tailoring their product and value propositions to the business problems of a particular client [Strambach, 2008; Aarikka-Stenroos, Jaakkola, 2012]. However, the development of such highly customized solutions requires active client involvement in both service co-production and value co-creation processes [Mustak, 2019; Cainelli et al., 2020]. In turn, as a result of these interactions an intensive knowledge creation and sharing between KIBS and their clients emerges. Thus, the latter receive access to the professional knowledge, experience and best practices accumulated by KIBS, while the former receive an opportunity to leverage their knowledge base by the new information related to markets, products and business processes of the clients [Heikka, 2020]. In addition, some new knowledge, i.e. not earlier possessed either by KIBS and their clients, may be jointly developed by them during the interaction [Grandinetti, 2018].

Knowledge directly shared by the client, developed by KIBS about the client, or jointly co-created by them during the co-production of service is a strategic asset for KIBS [Landry et al., 2012]. This 'client' knowledge enhances the main competitive advantage of KIBS as it helps them efficiently customize their products and services to the business needs and requirements of a particular client [Heikka et al., 2018]. Moreover, some researchers [e.g. Toivonen, Tuominen, 2009; Crevani et al., 2011] highlighted that KIBS are also characterized by the high relevance of ad-hoc innovations that are resulted not from planned R&D activities, but from the development of highly-customized solutions for business problems of the particular client. However, the impact of such daily project-related client interactions on the innovation activity of KIBS is significantly underexplored, while most of the existing studies in this field are focused only on formal cooperative client interactions (collaborations) [e.g. Cainelli et al., 2020]. To the best of the author's knowledge, this research is one of the first aiming at studying the impact of KIBS-client interactions during the 'routine' operational daily relationships on the innovation activities of KIBS firms.

The current thesis research is also one of the first empirical studies of the innovation activity of KIBS companies operating in Russia. The first specialized surveys of such companies in Russia were organized in 2006-2008 [Doroshenko, 2007; Doroshenko, Suslov, 2008] to study the current state and the prospects of the relevant industries4. Later, special attention was paid to the analysis of KIBS' crisis strategies [Doroshenko, 2010], their spatial distribution [Kotomina, 2016; Ivanov, 2016], and the process of public procurement of such services [Vinogradov et al., 2018]. The results of these studies are generally consistent with the findings of foreign researchers and confirm the positive impact of KIBS firms on the innovative activity of their clients and the high innovative potential of these companies themselves [Doroshenko et al., 2014]. However, there is a lack of empirical studies focusing on the exploration of the key drivers and barriers of innovation activity in Russian KIBS.

4 The detailed results of these studies are presented in [Doroshenko et al., 2010].

In addition, in recent years the development of Russian KIBS significantly slowed down due to the deteriorating economic and external political environment [Berezin, Doroshenko, 2015; Belousova, Chichkanov, 2016] as well as due to the COVID-19 crisis [Obshhestvo i pandemiya: opyt i uroki bor'by s COVID-19 v Rossii, 2020]. The facilitation of the innovation activity in KIBS industries is becoming an important challenge for the Russian economy as these firms may be a significant source of national economic growth [Gershman et al., 2018]. Besides, the development of KIBS industries and an increase of their innovation activity will also contribute to the achievement of the goals set by the President's Executive Orders5 and the Strategy for the Development of Services Exports until 20256 in terms of supporting digital transformation, boosting the competitiveness of Russian services at international markets, increasing the contribution of knowledge-based services to the total volume of Russian service exports and raising the share of Russian firms in world business services exports.

The research object is the innovation activity of KIBS enterprises.

The research subject refers to KIBS-client interactions being considered as one of the major factors of innovation activity in KIBS.

The research goal is to investigate whether KIBS-client interactions have an impact on the implementation of business innovations in KIBS.

To achieve this goal the following research tasks were established and implemented:

1. To determine the main features of KIBS companies and summarize the approaches for the identification of the industrial boundaries of KIBS;

2. To systematize the key drivers of KIBS' innovation activity;

3. To develop an approach for the empirical investigation of KIBS-client interactions represented by knowledge flows between two parties as a factor that may influence the innovation activity of KIBS;

4. To develop and empirically evaluate the model for the assessment of the relationship between KIBS' capacity to absorb knowledge7 during client interactions and their innovation activity;

5. To suggest managerial implications for KIBS firms, aiming at boosting their innovation activity by developing client knowledge absorptive capacity.

Methodology & Methods. To fulfill the first research task, a large set of papers devoted to the development of the KIBS concept, and to the determination of the industrial boundaries of KIBS, has been carefully reviewed and systemized. In addition, two main industrial statistical classifications that

5 Executive Order No 204 on the National Goals and Strategic Objectives of the Russian Federation through to 2024 (07 May 2018), Executive Order No 474 on the National Development Goals of the Russian Federation through 2030 (21 July 2020).

6 Approved by the Russian Government Resolution No1797-r of 14 August 2019.

7 The term 'absorptive capacity' was introduced by Cohen & Levinthal (1990) and refers to 'the ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends' [Cohen, Levinthal, 1990, p.128].

are the most frequently used in KIBS studies (NACE Rev. 2 and NAICS respectively) have been compared. Finally, it has been suggested that further empirical research should take into consideration the features of the national KIBS markets (in particular, the Russian one in this study) while identifying the industrial boundaries of KIBS.

To fulfill the second research task, a set of papers devoted to the exploration of patterns of innovation behavior and innovation strategies in KIBS was collected from the interdisciplinary scientific citation databases Web of Science and Scopus, using bibliometric tools. The main drivers of innovation activity in KIBS were identified based on the analysis of the selected papers. The significance of the identified factors was empirically tested by the application of the logistic regression technique to a set of the survey-based data collected by the HSE ISSEK in 2015 using a methodology that ensures the comparability of the results with international surveys of companies' innovation activity.

To fulfill the third research task, an approach that conceptualizes the process of KIBS-client interactions as a flow of knowledge between two parties [Miles, 2012; Zieba et al., 2019] has been employed. The concept of absorptive capacity has been used to study the impact of KIBS-client interactions on the innovative activity of KIBS companies. In addition, a special questionnaire has been proposed to assess the key dimensions of the client knowledge absorptive capacity in KIBS - i.e. their abilities to acquire knowledge during client interactions, to assimilate this knowledge, and to apply it for further usage.

To fulfill the fourth research task, a Research Model has been developed for the assessment of the relationship between the three dimensions of the KIBS' client knowledge absorptive capacity as well as other innovation drivers and innovation activity of KIBS. The process of data collection was supported by HSE ISSEK in 2019 as a part of the long-term project 'Monitoring of KnowledgeIntensive Business Services in Russia' and the author of the thesis research fully participated in the processes of the development of the survey methodology and tools. The logistic regression technique has been used to test the model in terms of both product and business process innovations.

To fulfill the fifth research task, the obtained results have been summarized and their implications discussed, and a set of practical recommendations aimed at stimulating KIBS' innovative activity by developing their ability to absorb knowledge during operational 'routine' client interactions have been suggested.

The author obtained the following main findings to be defended:

1. The KIBS sector can be fruitfully seen as consisting of three sub-segments representing companies specializing in technological, professional and creative activities and drawing on specific types of knowledge and thus possessing specific features.

Based on the results of the analysis of the literature devoted to the development of the KIBS concept the following key characteristics of the respective companies were determined:

• intangible nature of production;

• strong orientation on b2b markets and the provision of services for other companies, public entities and non-profit organizations, rather than for end-users;

• dual role of knowledge, which is both a key production factor (in the form of human capital and other elements of intellectual capital) and the main result of business activities;

• highly relational nature of activities in terms of the client involvement in the joint production of services and the high degree of their customization;

• high probability of creating ad-hoc innovations resulted from daily project-related activities rather than from specific research and development activities.

For further empirical analysis, the approaches to the determination of the sectoral boundaries of KIBS were systemized and generalized. It was revealed that the best statistical representation of KIBS sector is presented in the North American Industry Classification System (NAICS), where all the main activities traditionally related to KIBS are concentrated in a specialized section 'Professional, Scientific and Technical Services'. In turn, in the Russian Classification of Economic Activities (OKVED 2) which is also harmonized with the Statistical Classification of Economic Activities in the European Community (NACE Rev. 2), those KIBS specializing in business services in the fields of computer programming and information technology, are allocated in separate classes J62 and J63.

Due to the high level of heterogeneity of KIBS industries, for an additional control of the relevant industry effects, it is proposed to use a three-segment classification [see Miles, 2012], based on the differences in the set of types of knowledge and skills they use. The technological sub-segment (T-KIBS) includes companies whose main activities are related to the provision of services in the field of information technology (including software development), architecture, engineering, research and development. Professional KIBS (P-KIBS) are represented by companies providing legal, accounting, audit and management consulting services. In turn, due to the higher creative component of their activities, which involves knowledge about aesthetic and cultural issues, creative KIBS (C-KIBS) like advertising and marketing agencies are distinguished separately from P-KIBS.

To ensure international comparability, but taking into account the features of the Russian KIBS market, in this study those companies specializing in R&D services (OKVED 72) are excluded from further consideration. In Russia, state funds currently remain the main source of financing for internal expenditures on R&D, and most of the relevant organizations are characterized by state ownership [Science. Technology. Innovation. Pocket Data Book, 2021].

2. Access to external knowledge is one of the key drivers of the development and implementation of innovation in Russian KIBS.

Based on the results of the extensive literature review four major types of factors that may significantly influence the innovation activity of KIBS were identified. These factors are related to the creation of knowledge inside the companies, access to external knowledge sources, market and financial conditions. To empirically test the significance of these factors for Russian companies, four main hypotheses were developed:

H1.1: KIBS companies with a higher level of expenditures on human capital development are characterized by a higher level of innovation activity;

H1.2: The probability of creating and implementing innovative solutions is higher for KIBS companies with a wide regional network;

H1.3: The relationship between the level of standardization and innovation activity of KIBS companies is characterized by an inverse U-shaped relationship;

H1.4: Higher advertising and marketing expenditures are associated with higher innovation activity in KIBS.

To empirically test the hypotheses H1.1-H1.4, the following Research Model was developed: log —= a0 + A1* Human Capital¿ + Á2 * Branchesi + A3 * Standardizationi +

+ X4* Standardization2 + Á5 * Marketing Expenses¿ + A6 * Market Sizei + y1* Strategy¿ +

+ Y2 * T_KIBSi + y3 * C_KIBSi + y4 * Sizet + y5 * Agei + + Ei (1)

p ■

where reflects the probability that the firm i has implemented the particular type of

1 Pi

innovation; Human Capitalt, Branches¿, Standardization¿, Standardization2, Marketing Expenses¿, and Market Size¿ reflect factors that can have a significant impact on the innovative activity of the company i; Strategy¿, T_KIBSi, C_KIBSi, Size¿, and Aget are control variables, X1... X6 u y1... y5 - regression coefficients; a0 is a constant; Et is an error term. Detailed descriptions of all of these variables as well as their descriptive statistics are presented in Table 1. Table 1 - Definitions and descriptive statistics of variables used for the empirical assessment of the Research Model (1)

Заключение диссертации по теме «Экономика и управление народным хозяйством: теория управления экономическими системами; макроэкономика; экономика, организация и управление предприятиями, отраслями, комплексами; управление инновациями; региональная экономика; логистика; экономика труда», Чичканов Николай Юрьевич

Notes

1. The estimations are based on the last available official statistics by Federal State Statistics Service for 2018 and include NACE Rev.2 J (Information and Communication) and M (Professional, scientific and technical activities) industries (Rosstat, 2020).

2. The estimations are based on the last available official statistics by Federal State Statistics Service which is 2017 for regional GDP and 2018 for the number of registered companies (Rosstat, 2020).

3. Most of the dependent variables are binary ones, thus almost all of the models were empirically evaluated using logistic regressions. The only exception is model 1, with an index-based depended variable reflecting the innovation intensity; this was evaluated by applying an OLS regression. For this model, regression coefficients and R2 are presented, while for models 2-8 Tables 1 shows marginal effects, Nagelkerke R2 and the share of correct predictions.

4. A brief overview of the recent special issue devoted to the impact of big data analytics on the different aspects of firm performance and value creation is presented in Singh & Del Giudice (2019).

Список литературы диссертационного исследования кандидат наук Чичканов Николай Юрьевич, 2021 год

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