Predicting Organizational Behaviour of Public Research Institutions Over Uncertain Scenarios

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Predicting organizational behaviour of public research institutions over uncertain scenarios

Mario Coccia

National Research Council of Italy CERIS-CNR via Real Collegio, n. 30, 10024 Moncalieri (Torino) - Italy Tel.: +39 011 68 24 925; fax : +39 011 68 24 966 [email protected]

ABSTRACT : The purpose of this paper is to analyse and forecast, by a demographic perspective, the organizational behaviour of human resources into public research labs. The research focuses on the biggest Italian public research body. Demographic models of growth, based on different human resource policies, show the uncertain and retrogressive evolutionary change of Italian public research bodies that, ceteris paribus, would halve their research personnel over the forecast horizon. These results provide vital information to the public management about the organizational weaknesses and environmental threats for internal demographic trend in order to support managerial decisions for improving the strategic change and survival of public research institutions over time.

KEYWORDS : Organizational Studies, Forecasting, Public Research Institutions, R&D Management, Hu- man Resources.

JEL-CODES : I20, J11, J26

The author thanks Philippe Laredo (Université Paris-Est, IFRIS & LATTS, France) and Thed N. van Leeuwen (Cen- tre for Science and Technology Studies, Leiden University, Leiden, The Netherlands) for helpful comments and sug- gestions, as well as Emanuela Reale (Ceris-Rome) and 3 rd ENID (Paris, 3-5 March 2010) conference participants for useful discussion. Silvana Zelli and Diego Margon provided capable research assistance. A draft version of this paper has been included in the working paper series of my institute. I gratefully acknowledge financial support by the Ital- ian National Research Council. Usual disclaimer applies.

Biographical notes : Mario Coccia is an economist at the National Research Council of Italy (Ceris-CNR), and visiting pro-

fessor of industrial organization at the University of Piemonte Orientale (Italy). He has been research fellow at the Max

Planck Institute of Economics (Germany), visiting professor at the Polytechnics of Torino (Italy), visiting researcher at the

University of Maryland (College Park, USA) and Institute for Science and Technology Studies at the University of Bielefeld

(Germany). He has written extensively on Economics of Innovation, Technometrics, Management and Evaluation of Public

Research Labs; his research publications include more than one hundred and fifty papers in seven disciplines.

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Predicting organizational behaviour of public research institutions over uncertain scenarios

Author

Affiliations

KEYWORDS : Organizational Studies, Forecasting, Public Research Institutions, R&D Management, Hu- man Resources.

JEL-CODES: I20, J11, J26

The author thanks …..

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1. INTRODUCTION

Scientific research is a crucial competitive asset for nations in the current knowledge era (Chiesa and Frattini, 2009, chps. 1, 3 and 7). It is produced and spread by public and private research institutions that are core elements in the national system of innovation 1 to support the “competitive advantage” of countries (Porter, 1990; see also Aghion and Howitt, 1998; Author, 2005). Research organizations, as all economic subjects, are affected by political changes, turbulent markets, economic downturns, and other environmental pressures that have been generating a “strategic change”2 of these complex entities in modern economies. In order to analyze the organizational behaviour of research organizations and to design apt R&D management implications, it is critical to forecast the behaviour of their human R&D resources over time. The purpose of this organizational study is to analyze the future dynamics of human resources operating within public research organizations by some demographic models. This research focuses on the biggest Italian public research body: the National Research Council of Italy (CNR), an institution similar to other European research bodies operating in France, Spain, Germany, etc. (see Author, 2001, 2004, 2008, 2009). The results can help to understand the organizational weaknesses and environmental threats of these vital research bodies over the forecast horizon (periods between today and the date of forecast), in order to support rational decisions of policymakers and public R&D managers for improving their “strategic change” as well as ensuring their survival over time.

1 The national system of innovation (NSI) refers to the complex network of agents, policies, and institutions supporting the process of technical advance in an economy (Lundvall, 1992). The narrow definition of NSI would include the subsystem research sector represented by universities, research laboratories, while the broad NSI includes many subsystems such as finance, firms, government, and so on. The efficiency of this broad NSI supports economic growth patterns. 2 Gioia and Chittipeddi (1991, p. 433, passim ) argue that “change involves an attempt to alter the current way of thinking and acting by organization’s membership. More specifically, strategic change involves an attempt to change current modes of cognition and action to enable the organization to take advantage of important opportunities or to cope with consequential environmental threats” ( original emphasis ).

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2. THEORETICAL BACKGROUND

Scientific knowledge is the core element that an R&D lab expects from its human capital. Chiesa and Frattini (2009; p. 110) point out that the literature about the human resources in R&D is not very developed, although this function plays a critical role for effective and efficient organizations in public and private contexts ( cf. also Costas et al., 2009). R&D people are special type of knowledge workers, and human resources management in public research labs should pay attention to dynamics of hiring and retirement over time in order to monitor and ensure the survival of these main organizations that support the competitiveness of modern economies ( cf. Lundvall, 1992; Aghion and Howitt, 1998). The demographic models applied to organizational studies can be useful to analyze and predict the behaviour of human resources to support a “strategic change” of research organizations in turbulent and unstable markets. Demography in organizational settings involves the work force of organizations, especially its turnover and mobility (Bourdieu, 1988). Recent works in this tradition addresses issues such as the sex segregation in jobs, fragmentation of work, and the opportunity structure within organizations (Carroll and Hannan, 2000; Palomba, 2001; Calcatelli et al., 2003). A main topic of the demography of organizations is called internal organizational demography (cf . Carroll and Hannan, 2000, Chp. 2, pp. 32-35). Pfeffer (1983, p. 303) defines demography as “the composition, in terms of basic attributes such as age, sex, educational level, length of service, race and so forth of the social unit under study . . . . the demography of any social entity is the composite aggregation of the characteristics of the individual members of that entity”. “ ‘Pfeffer also advances . . . propositions about the causes and consequences of demographic phenomena in organizations. . . . [such as] proprieties of demographic distributions of persons in the focal organization, especially the tenure or length of service (LOS) distribution of members of the organization’ ” (Carroll and Hannan, 2000, p. 33). Some interesting topics analyzed are the consequences of the LOS distribution on some organizational outcomes, e.g. employee (see Carroll and Hannan, 2000, pp. 33ff). However, organizations are constructed social and economic entities, not biological organisms. Some approaches of human and biological demography can be borrowed,

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others require to be accommodated to social and economic nature of organizations (Carroll and Hannan, 2000). In fact, demography of organizations should consider, according to Carroll and Hannan (2000, pp. 35ff) the following main differences between organizations and biological organisms: − Variety of events that define organizational births and deaths; − Potential immortality of formal organizations that can persist as an social entity long after its initial members have departed; − The lack of parentage for organizations; − The intellectual (and organizational) rather than biological and genetic transmission of information and routines; − Heterogeneity of organizational populations; − The ability of organizations to change populations and transform themselves.

In particular, the demographic analysis applied to research organizations can be important in order to analyze the organizational behaviour of human resources and to support their rational management as well as “strategic change” 3. Before analyzing and discussing the organizational behaviour of human resources operating within Italian national research council (CNR), let me describe its morphology and the methodology of research. Some organizational best practices for improving the management of R&D people conclude this paper.

3. MORPHOLOGY OF ITALIAN NATIONAL RESEARCH COUNCIL (CNR)

The morphology (organization) of Italian National Research Council (CNR) has been affected by Italian research policy, which has been changing according to governments’ changes. The organizational changes of the CNR are mainly due to the first reform, in 1999, based on consolidation of research units in order to increase the efficiency through larger sizes. Now there are about 100 new institutes, which often have several decentralised units spatially located in different cities. While this reform was still under way, in 2003, after the political elections, the government decided to launch a new restructuring based on project management , with an explicit aim of transforming the

3 It is important to note that the analogy between human populations and organizations is noticeable,

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CNR institutes in entrepreneurial bodies that supply technological services to firms and other external users (see Author and Mister X, 2008; Author, 2009). Common features of these public management reforms are the shrinking public research unit budgets for reducing high public Italian debt with a main consequence: now the public funds are no more sufficient to cover current expenses of public research institutes. In addition, low availability of public funding during the current economic recessions and market turbulence have also been reducing hiring and physiological turnover of payroll research such that several lines of research and research units have been dismissed and/or downsized. Therefore, research institutes are forced to apply for market funds to conduct normal scientific activities as well as to recruit term-contract research personnel. Although researchers spend a huge amount of time to supply technological services, for preparing grant applications, managing grants, and so on, reducing in this way the time to carry out fundamental scientific research, the market (external) funding is now the main financial resource for Italian public research institutes (see Author, 2009). This strategic change of public research units is functional to cope with environmental threats owing to low public funds in turbulent markets (see also Author and Mister X, 2007; 2008; Laudel, 2006). This scenario is present not only in Italy but in several countries such as Germany, Australia, Norway (Laudel, 2006), Spain (Sanz-Menéndez and Cruz-Castro, 2002) etc. In fact, the objectives of restructuring the Italian public research institutions were to reduce general costs and to increase their efficiency and technology transfer. In consideration of the widely shared political objective of improving scientific research production and technology transfer in public institutions of an industrialised country, such as Italy, the organisational reforms of the CNR were poorly designed in the implementation phase, such that have been generating bureaucratization and organizational issues, e.g. internal financial crisis that threat the future survival of several research lines and units ( cf . Author and Mister X, 2007; 2008). Next section describes the methodology of research based on demographic models that provide vital information to analyze and forecast the organizational behaviour of public research bodies. although may be a forced approach in some cases.

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4. DEMOGRAPHIC APPROACH FOR FORECASTING THE ORGANIZATIONAL BEHAVIOUR OF HUMAN RESPOURCES IN PUBLIC RESEARCH INSTITUTIONS

Data of this research are the human resources operating within the CNR (see CNR Report, 2007). A first main aspect is to analyze the rate of growth of the research personnel that can be calculated by different approaches ( cf. Livi Bacci, 1999, chp. 3): a) Population is that at beginning of the time interval t (rate of arithmetic growth: ar );

If the amount of population at beginning is aP and at the end of the period is tP and the time interval is equal to t, the rate of arithmetic growth ar is given by the following equation:

a a t P=0 P+0 P( r ⋅ )t where of t P−0 P=0 P ⋅r ⋅t and hence P− P ar = t 0 = rate of arithmetic growth 0 P ⋅t

b) Population is that existing at beginning of each yearly period forming the time interval t (rate of geometric growth: gr); in this case, equation of the population development obeys to the formula of geometric growth:

  P= P ⋅ 1+gr t of which t P g t 0 ( ) Log   = t ⋅ Log ()1+ r  0 P 

 P   t  Log   g  0 P  g Log ()1+ r = therefore r is obtained by the exponential transformation. t

c) Population is that existing in each time interval infinitely small (rate of growth compound continuously: r). In this case, the function of population development is exponential one:

rt t P=0 P ⋅ e where e is the base of natural logarithm (2.71828…).

 P   t  Log   t P r t t P  0 P  Hence = e ; Log = r ⋅ t ; r = . 0 P 0 P t

This case is often used in the demographic analysis as forecasting approach in the medium run 4.

4 See Diebold (2004) for a complete presentation of other forecasting methods.

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These demographic methods offer an analytical framework for the organization theory and institutional analysis in order to analyze the organizational behaviour of R&D human resources within public research organizations.

5. PREDICTING ORGANIZATIONAL BEHAVIOUR OF HUMAN RESOURCES WITHIN PUBLIC RESEARCH INSTITUTIONS UNDER TEMPORAL UNSTABLE GROWTH

First of all, the spatial distribution of the CNR research personnel is displayed in the table 1 that also shows the average age per macro region. Last column of table 1 shows as the CNR has a human capital mainly based on senior research personnel (over than 43 years). Figure 1, instead, shows the typical pattern of public recruitment in Italian research institutions that has an unstable behaviour over time. In fact, the irregular recruitment path is due to hiring-block applied by governmental budget laws in order to reduce the huge Italian public debt.

TABLE 1: SPATIAL DISTRIBUTION OF CNR RESEARCH PERSONNEL - YEAR 2004

CNR research personnel Average age Macro regions units* (Years)

North Italy 1,889 48 Central Part of Italy 2,752 49 South Italy 1,468 44 Italian Islands 541 43 Total 6,650 47

*Researchers and Technicians

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1600

1400

1200

1000

800

600

400

Number hiringof over time 200

0 1958 1962 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 Year

FIGURE 1: UNSTABLE HIRING GROWTH OF CNR RESEARCH PERSONNEL

If the following assumptions are stated:

1: aP is the research personnel of the CNR at 1995

2: tP is the research personnel of the CNR at 2005 3: t is the period of the human resource policy and it is equal to 10 years 4: Human Resource Policy ( HRP ) over Forecast horizon ]t+n onwards[ (e.g. from 2011 onwards) is similar to HRP over [t; t+n ], i.e . [1995; 2005]

Table 2 shows, ceteris paribus , the arithmetic, geometric and exponential rates of growth of the CNR research personnel over time. The rates of growth display a declining trend of CNR research personnel over 1995-2005, that is higher if the hiring of 2001 (peak in figure 1) is not considered: −3.63% vs. −0.70% (see last column in table 2). TABLE 2: CNR PREDICTED DEMOGRAPHIC RATES OF GROWTH OVER 1995-2005

Year 1995 2005 Research Personnel of CNR 7,451 6,945 (number of units) Rate Rate % ar = Arithmetic growth 1995-2005 −0.0068 −0.68 gr = Geometric growth 1995-2005 −0.0070 −0.70 r = Exponential growth 1995-2005 −0.0070 −0.70 r’ = Exponential growth 1995-2005 without 2001* −0.0363 −3.63

*Note : Hiring in 2001 is 1,570 employees

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These vital results are important to forecast when the research personnel of CNR will be halved over the forecast horizon, considering the policy of human resources applied by Italian Governments over 1995-2005 period (which is characterized by expansion and restriction phases of hiring). Figure 2 displays three main scenarios considering the exponential growth, which is an apt model, ceteris paribus , for forecasting the organizational behaviour of human resources (of public research bodies) over the forecast horizon.

Pessimistic Normal Optimistic scenario scenario scenario

Research aP P/2 P/2 personnel a a a P/2

Years t0 2024 2073 2103 ORECAST ORIZON F H

Note : aP = Research personnel at time t 0 ; aP/2 = Research personnel halved

FIGURE 2: HALVING OF CNR RESEARCH PERSONNEL ACCORDING TO DIFFERENT SCENARIOS

In particular, the three main environmental scenarios forecasted, ceteris paribus , are (see figure 2): a) Optimistic scenario of R&D people increase: it is based on a future expansive human resource policy, including the high number of hiring of 2001. The growth model provides the following results:

−0.693147 1/ 2 = e r×t ln; 1/ 2 = −0.00703 × ;t = ;t − 0.00703 t = 98 .56 ≅ 98 years Therefore, the research personnel of the CNR would be halved, ceteris paribus , in the year 2103 (= 2005 + 98 years). b) Pessimistic scenario of R&D people reduction: this scenario based on future restrictive human resource policy with low hiring (similar to the current period): i.e. if data do not consider the extraordinary hiring in 2001 year of 1,570 research

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personnel units, mutatis mutandis, the result is ≅ 19.10 years and the critical year is 2024, when the research personnel of the CNR would be the half of that of 2005.

c) steady-state growth of human resources: this environmental scenario is based on future human resource policy with a steadier pattern of hiring and normal turnover of the research personnel: i.e. as the year 2001 has been an year of exceptional expansion of hiring, the analysis is repeated considering the payroll personnel of CNR over 1991-2000, before the year 2001. In this case the rate of exponential growth is −9.47‰ and applying the model of growth with this rate, the population of the CNR would be halved in the year 2073.

Considering these environmental scenarios based on different human resource policies (Fig. 2), public management can work out three strategies in order to maximize the benefits for public research institutions: 1) maximize the hiring in the optimistic environmental situation based on the best scenario a) ; 2) minimize the losses of hiring and research personnel by a provident behaviour that considers the worst scenario b) ; 3) maxmin is a mix strategy of two previous ones, considering the normal environmental situation of the scenario c).

Table 3 and 4, instead, show the dynamics of research personnel, considering researchers, technicians and administrative staff (tab. 3) as well as payroll and term- contract research personnel (tab. 4). TABLE 3: CNR PERSONNEL PER ACTIVITY OVER 1997-2005 PERIOD

Year Researchers Technicians Administrative Total 1997 3,600 2,836 1,066 7,502 1998 3,635 2,827 1,022 7,484 1999 3,625 2,730 1,031 7,386 2000 3,650 2,689 1,038 7,377 2001 4,319 2,643 1,120 8,082 2002 n.a. n.a. n.a. n.a. 2003 n.a. n.a. n.a. n.a. 2004 4,146 2,248 671 7,065 2005 3,704 1,947 639 6,290 Note : n.a. = not available data

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TABLE 4: CNR RESEARCH PERSONNEL BY TYPE OF CONTRACT OVER 1991-2001 PERIOD

% Year Payroll Term contract Total of term-contract personnel 1991 6,884 n.a. n.a. - 1992 6,846 n.a. n.a. - 1993 n.a. n.a. n.a. - 1994 6,595 n.a. n.a. - 1995 6,408 1,041 7,449 13.98 1996 6,333 1,118 7,451 15.00 1997 6,234 1,248 7,482 16.68 1998 6,419 1,065 7,484 14.23 1999 6,314 1,072 7,386 14.51 2000 6,262 1,115 7,377 15.11 2001 7,615 467 8,082 5.78 Note : n.a. = not available data

In addition, figure 3 shows the exponential rates of growth considering the activity of CNR research personnel over 1997 - 2005. This figure suggests that the forecasted negative growth of human resources in CNR is mainly due to higher negative rate of growth of technicians (−18.1‰) and in particular administrative staff (−24.7‰).

Researchers 3.0 +1.4

-2.5

-8.0

-13.5

-19.0 Technicians −18.1 Rate of exponential growth Rate ‰ -24.5 Administrative −24.7 -30.0 1997-2005 period

FIGURE 3: EXPONENTIAL GROWTH (‰) OF RESEARCH PERSONNEL OVER 1997-2005

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6. MAIN LESSONS LEARNED

The purpose of this research is to apply a demographic approach for forecasting the organizational behaviour of human resources into public research labs. This approach suggests to policymakers vital information to support rational decisions aimed at reinforcing the survival and strategic change of public research bodies in turbulent markets. The main lessons learned by this demographic analysis applied to Italian CNR are: The CNR has a structure of rather old research personnel (table 1); The predicted average rates of growth of research personnel have negative values such that there will be a halving of CNR Research Personnel over the forecast horizon (see table 2); With the optimistic scenario ( a) based on expansive human resource policy of hiring, the research personnel would be halved by 2100 or thereabouts, whereas the pessi- mist scenario ( b) generates this result in the 2024, instead the steady-state scenario (c) shows as critical year the 2073 (Fig. 2); This declining trend of CNR research personnel is mainly due to higher negative rate of growth of technicians and in particular administrative staff (Fig. 3).

These negative forecasting trends of the research personnel are due to low public investment in research sectors by Italian Governments and as consequence low hiring of research personnel in current contexts of market turbulence, uncertainty, and global economic recessions. The main effects of this research policy are that a large amount of young researchers is now working in the CNR labs (as in the Italian universities) with short-term contracts and very low future perspectives; in addition, several lines of research as well as research units have been dismissed and/or downsized. The hiring- blocks have also other two negative aspects: brain drain and adverse selection . In general the best researchers do not wait long term to be hired in public research labs and go towards foreign research labs/universities, generating a growing unidirectional flow towards the most advanced countries ( e.g. The USA and Europe essentially) that represent for Italy a net economic and scientific loss. The remaining researchers survive with short-term contracts, and in the long-run , under the pressure of trade unions, they arrive to a tenured position in advanced age (about forty-year-old). This dynamics

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generates negative effects in the production of scientific and technical knowledge of public research institutes. In fact, current human resources policy of Italian CNR has hired, by tenure track, 778 units of term-contract researchers and published new researcher positions in 2010 that the Italian government’s €24.9bn deficit-cutting measures for 2010-2012 have been stopping until the 2013 in order to reduce huge public debt and to ensure the objectives of reining in public spending (table 5 and figure 7).

TABLE 5: CURRENT RESEARCH POLICY OF CNR

Research personnel hiring*

Tenure track Hiring new researcher positions 2010 Total 2007-2010

778 units 485 units* 1,263

Note: * Italian Government is going to stop the turnover and therefore these positions in order to reduce public Italian debt in the current financial turbulence of markets

9000 2011-2014 8000 ~7209 units 7000

6000

5000

4000 2010 3000

2000 Number ofNumber research personnel 1000

0 −−−3.25% −−−10.8% Percent reduction -1000 in comparison with 2011-'14 1995 2001 2010 2011 Year Research personnel Reduction in % of 2011

FIGURE 7: FORECAST OF RESEARCH PERSONNEL AND ITS REDUCTION IN COMPARISON WITH OTHER PREVIOUS YEARS

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The tenure track policy of CNR should partially limit some negative aspects showed and extend the critical year of halving the research personnel in different scenarios, however the negative sides of current R&D human policy by Italian CNR are mainly due to: The lack of interest by bureaucrats and politicians about organizational development of public research laboratories and their staff; Political pressures by some trade-union lobbies for increasing the number of research personnel rather than efficiency of payroll researchers, in a context of shrinking public research lab budgets and market turbulence.

This analysis confirms that current economic and research policy, designed by Italian Governments, has been affecting in negative way the evolutionary change of public research units, generating problems for furthering of research and threatening their survival in the long run. The origin of this situation in Italy is rooted within the lack of a long-term national research strategy and of a consistent research policy (shared by Italian governments of different political coalitions), which has been generating structural deficiencies for public research institutions. Therefore, this uncertain and ambiguous Italian research policy for human resources development into public research bodies, in a context of low public funding and financial turbulence, is not a sustainable strategy for long-term scientific objectives!

7. MODERN R&D MANAGEMENT IMPLICATIONS FOR IMPROVING THE EFFICIENCY OF PUBLIC RESEARCH LABS OVER UNCERTAIN SCENARIOS

The uncertain Italian research policy, based on a myopia of short-run targets ( e.g. massification) 5 and public funding reductions rather than long-run scientific goals, has been creating problems of structural deficiencies and financial crisis within the public research organizations. Unless this current public management of research units is revised, main public research units and research fields will be dismissed and as

5 Because of market-oriented trends of research units - due to low public funds- they are focused on massive increase in technological services rather than fundamental research, therefore there is depersonalisation of researchers and emptying of the scientific research activity of its main contents: i.e. less discovery-based research around longer term needs centred on public welfare; in other words, business and commercial interests are influencing research units and universities in an unsavoury manner, see Musselin, 2007; Schuetze, 2007.

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consequence “important portions of scientific knowledge will be private property and fall outside the public domain, and] that could be bad news for future progress of science and for technological progress” (Nelson, 2005). The efficiency increase of public research bodies, under uncertain scenarios based on restrictive public funding and stop of public recruitment policy that will halve the future R&D human capital in this period of austerity, can be achieved improving the management of current R&D people. In primis , modern R&D labs are now relying on cross-functional teams in order to improve cooperation among different researchers focused on the same objectives, although spatially located in different places (cf. Bartlett and Ghoshal, 1989). Moreover, critical R&D management implications, to optimize and rationalize human resources, should be ( cf . Chiesa and Frattini, 2009, Chp. 3): Create an adequate environment within the institutes which allows to researchers, interpersonal relationships that have cross-fertilization effects for scientific production (Chiesa and Frattini, 2009, chp. 3). Reinforce the “idea generators” (Roberts and Fusfeld, 1981) that are considered the most fundamental category of R&D people ( cf. also James, 2002, Chiesa and Frattini, 2009). The new research institutes can expect relevant contributions from this “star scientists”. Foster “Team leaders” that act as catalysts by allowing institute staff to participate in research projects, facilitating internal communication: leading rather than commanding and controlling should be the modern approach of team leaders. Kayworth and Leidner (2002) argue that their role is very important, especially when the workforce, as in the current institutes of CNR, is geographically dispersed and R&D workers have to collaborate in cross-functional teams. Design a reward scheme for human resources by flexible salaries, paying outstanding performers more than other workers. Kochanski and Ledford (2001) claim that without any differentiation in extrinsic rewards, as in the current CNR, high performers would feel dissatisfied and leave and/or working less if treated in the same way as low performers. These best practices should reduce the brain drain that represents a sunk cost and loss of tacit knowledge accumulated over time in the institutes of CNR.

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Find a good equilibrium between Locals and cosmopolitans R&D workers for increasing the research performance of public research labs. “Locals” have managerial attitudes but they present less technical skills: self-identification is more with the organization than scientific work. “Cosmopolitans” researchers are more technically-oriented and consider freedom of research to be highly important, and identify themselves with their profession ( cf. Aryee and Leong, 1991; Womack and Jones, 1994); however the risk to avoid is that this latter category can be isolated from the rest of the organization ( cf. Allen and Katz, 1992). Have a top management that carries out the critical function of “ambassador role” (Ancona and Caldwell, 1992), more and more important in turbulent context, addressed to link insiders and outsiders subjects. Modern public R&D managers should shift from a command and control approach to a leadership-oriented approach: public managers should not act as “captains” but as “catalysts" ( cf . Hammer and Champy, 1993; James, 2002). In addition, public R&D workers should be encouraged to achieve scientific goals but also business and financial objective. Create stimulating work environment (clear objectives, collaborative teams, fluent communication, opportunity to growth and fair reward system linked to scientific productivity) in order to increase the scientific performance of public research labs. In addition to leadership and scientific skills, some administrative and financial competencies should also be developed by researchers in order to make their current work more efficient (Chiesa and Frattini, 2009, p. 119). Reduce sources of conflicts and misunderstandings within the research organization. In fact, lack of organizational communication can hurt or frustrate individual creativity, cause lower performance and lead to dissatisfaction and stress (Tsui et al ., 1992, Cordero et al ., 1996, quoted by Chiesa and Frattini, 2009, pp. 120-121). Top management should foster work involvement and job satisfaction of its research groups since these are key elements to increase scientific performance of public research institutes in uncertain and turbulent contexts ( cf. Author, 2001a).

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Although this analysis focused on Italian case study cannot be transferred directly to other countries, the worldwide tendency in research sector seems to be convergent in several countries, since globalization generates economic recessions and market turbulence across countries that, by austerity packages, reduce public investment and, as consequence, affect organizational behaviour of public research bodies. Lessons learned by this paper and R&D management implications for human resources are a critical basis to a great extent relevant to policymakers in order to support the correct strategic and evolutionary change of public research units in knowledge era. In addition, the governments have to be aware of the risk of hasty reforms and myopia of current research policies that do not consider a scientific and human resources development in the public research bodies. The threat is that with the declining trend of public research personnel and funding, certain types of main research institutions might become “‘endangered species’ in science” (Laudel, 2006, p. 503). No doubt that to support provident science policy, further research about this new western-style organizational behaviour of public research institutions is needed to strengthen this important topic in economic and managerial literature in order to improve the management of R&D people in public research labs that has, more and more, a driving role for modern competitiveness based on intangible capital.

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