BALANCING EXPLORATION AND EXPLOITATION IN
ALLIANCE FORMATION
DOVEV LAVIE
University of Texas at Austin
LORI ROSENKOPF
University of Pennsylvania
Do firms balance exploration and exploitation in their alliance formation decisions
and,if so,why and how?We argue that absorptive capacity and organizational inertia
impose conflicting pressures for exploration and exploitation with respect to the value
chain function of alliances,the attributes of partners,and partners’network positions.
Although path dependencies reinforce either exploration or exploitation within each
of these domains,we find that firms balance their tendencies to explore and exploit
over time and across domains.
Scholars studying exploration and exploitation
in organizational learning have assumed a strategic
posture by recognizing the essential trade-offs firms
make in undertaking these activities,yet little is
known about the organizational mechanisms that
drive firms’tendencies to engage in either activity
or about whether and how firms balance the two
activities.The fundamental conceptualizations
highlighting the merits of balancing conflicting
needs for exploration and exploitation (Levinthal &
March,1993;March,1991)have been incorporated
only in simulation studies (e.g.,Levinthal,1997;
Rivkin &Siggelkow,2003)or elucidated by anec-
dotal evidence (e.g.,Tushman &O’Reilly,1997).
Studies such as those cited have noted that alter-
native organizational forms,such as decentralized versus centralized structures and organic versus mechanistic ones,are better suited for engaging in either exploration or exploitation within firms’or-ganizational boundaries (Brown &Eisenhardt,1997;Nickerson &Zenger,2002;Siggelkow &Levinthal,2003).However,they do not address the question of balance in interfirm relationships.Sim-ilarly,a host of empirical studies in the alliance literature have struggled to identify industry con-ditions or clusters of firms that demonstrate ten-dencies to either explore or exploit,paying less regard to whether balance can be achieved.We attempt to fill this gap in organizational learning research by offering theory and evidence that dem-onstrate why and how firms balance these tenden-cies over time and across domains.We focus on the challenges of balancing explora-tion and exploitation in alliance formation deci-sions (Koza &Lewin,1998)following the growing interest in interorganizational learning.In this con-text,most studies have focused on external indus-try forces,suggesting that turbulence and market uncertainty may generate either exploitation (Beck-man,Haunschild,&Phillips,2004;Rothaermel,2001b),exploration (Rowley,Behrens,&Krack-hardt,2000),or both (Koza &Lewin,1998).Park,Chen,and Gallagher (2002)noted that only re-source-poor firms form exploitation alliances in turbulent industries.Yet even studies that examine firm characteristics have produced mixed evidence on the antecedents of exploration and exploitation.For instance,Rothaermel and Deeds (2004)noted that exploitation increases with firm size,whereas Beckman and her coauthors (2004)showed that firm size also contributes to exploration.These
We thank special issue coeditor Ken Smith and three
anonymous AMJ reviewers for their helpful comments.
We benefited from the feedback received from Ranjay
Gulati,Pam Haunschild,George Huber,Dan Levinthal,
Toby Stuart,and Jim Westphal.Additional feedback was
received from participants in the 2005Harvard Business
School Corporate Entrepreneurship Conference and par-
ticipants of management colloquia held at the Wharton
School,University of Pennsylvania,and the McCombs
School of Business,University of Texas at Austin.We
also thank Christopher Ray and Mike Hendron for their
research assistance.The data used in this study were
derived primarily from Dovev Lavie’s doctoral disserta-
tion,“The Interconnected Firm:Evolution,Strategy,and
Performance”(University of Pennsylvania,2004).We are
grateful for the financial support received from the Mack
Center for Technological Innovation at the Wharton
School.An abbreviated prior version of this paper was
published in the Best Paper Proceedings of the 2005
annual meeting of the Academy of Management,in
Honolulu.
?Academy of Management Journal
2006,Vol.49,No.4,797–818.
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studies offer interesting insights but focus on dif-ferent conceptualizations of the exploration-exploi-tation construct.
We posit that prior research on the antecedents of exploration and exploitation has produced incon-sistent evidence because each study examined ex-ploration and exploitation within a single domain, disregarding the conflicting organizational pres-sures that influence learning in various domains.In this study,we explicitly distinguish three domains in which exploration and exploitation can be pur-sued and balanced.The alliance literature has tra-ditionally associated exploration and exploitation with the value-adding activities of alliances—that is,the value chain function that they serve—thus conceptualizing a“function domain.”Taking this course,researchers have identified knowledge-gen-erating R&D alliances as exploration alliances and knowledge-leveraging marketing alliances as ex-ploitation alliances(Koza&Lewin,1998;Rothaer-mel,2001b).Setting a somewhat different course, we also encompass the network positions of part-ners(conceptualizing a structure domain)and their profiles(conceptualizing an attribute domain). Structure exploration refers to a firm’s decision to form alliances with partners with whom it has no prior ties(Beckman et al.,2004),whereas attribute exploration refers to a firm’s forming alliances with partners whose organizational attributes consider-ably differ from those of its prior partners.In our framework,we further acknowledge the interde-pendence between exploration and exploitation (Levinthal&March,1993)by conceptualizing these activities as resting on a single continuum rather than prevailing as two independent organizational choices.
Our main contribution to theory involves delin-eating distinct domains of exploration-exploitation and advancing the notion that firms balance explo-ration and exploitation over time within domains as well as across these domains.For example,a firm may engage in an R&D alliance(function ex-ploration)with a prior partner(structure exploita-tion)who differs in size and industry focus from the firm’s other partners(attribute exploration). Moreover,a firm may shift from exploitation to exploration or vice versa within domains over time (e.g.,transitioning from prior partners to new part-ners).To further advance this theory,we supple-ment the traditional focus on external industry forces by arguing that firms face internal organiza-tional pressures for exploration-exploitation. Whereas organizational inertia(Hannan&Free-man,1984)fosters exploitation,absorptive capacity (Cohen&Levinthal,1990)encourages exploration. We posit that although firms encounter challenges in balancing these conflicting pressures within do-mains,they can reconcile these pressures by dy-namically balancing exploration and exploitation across domains.Our analysis of a comprehensive sample of alliances formed by United States–based software firms between1990and2001provides empirical support for these ideas.
THEORY AND HYPOTHESES
The exploration-exploitation framework distin-guishes two broad patterns of learning behaviors. March defined them as follows:“Exploration in-cludes things captured by terms such as search, variation,risk taking,experimentation,play,flexi-bility,discovery,innovation.Exploitation includes such things as refinement,choice,production,effi-ciency,selection,implementation,execution”(1991:71).Levinthal and March added that explo-ration involves“a pursuit of new knowledge,”whereas exploitation involves“the use and devel-opment of things already known”(1993:105).More recently researchers have elaborated these ideas by considering their implications not only for intra-but also for interorganizational learning(e.g.,Child, 2001;Grant&Baden-Fuller,2004;Holmqvist,2003; Ingram,2002;Lane&Lubatkin,1998;Larsson, Bengtsson,Henriksson,&Sparks,1998).They have recognized that collaboration with partners facili-tates learning by accessing new knowledge residing outside a firm’s boundaries and by collaboratively leveraging existing knowledge with partners.Thus, alliances,which are voluntary arrangements among independent firms involving exchange,sharing,or joint development or provision of technologies, products,or services(Gulati,1998),have become a noteworthy vehicle for exploration and exploitation. The Three Domains of Exploration-Exploitation in Alliance Formation
We identify three separate domains of explora-tion and exploitation that together describe an alli-ance.We begin by asking three questions:What is the value chain function of the alliance(function)? Whom does the focal firm partner with(structure)? To what extent does the firm’s partner differ from prior partners(attribute)?Table1summarizes these distinctions.
Function exploration-exploitation.The explora-tion-exploitation framework was introduced in the interorganizational context by Koza and Lewin (1998),who noted that firms may form alliances to exploit existing knowledge or to explore new op-portunities.Subsequent research has thus focused on the value chain function that alliances serve
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(Koza&Lewin,2000;Park et al.,2002;Rothaermel, 2001b;Rothaermel&Deeds,2004).Firms that en-gage partners in R&D that may lead to innovative technologies and applications can be said to partic-ipate in exploration,whereas firms that rely on alliances for commercializing and using existing technologies or employing complementary partner capabilities undertake exploitation.In this sense, exploration alliances engage in upstream activities of the value chain,enabling partners to share tacit knowledge and develop new knowledge.In con-trast,exploitation alliances engage in downstream activities such as commercialization and marketing that leverage and combine partners’existing capa-bilities through exchanges of explicit knowledge (Rothaermel,2001b).The distinction between ac-quiring and generating new knowledge through ex-ploration and accessing,integrating,and imple-menting existing knowledge through exploitation (Grant&Baden-Fuller,2004)has been thus linked to firms’polar tendencies to engage in R&D alli-ances versus marketing alliances(Park et al.,2002; Rothaermel,2001b;Rothaermel&Deeds,2004). Structure exploration-exploitation.The struc-ture domain of exploration-exploitation takes into account the network positions of a firm’s partners. Recurrent alliances between firms are considered a form of exploitation,and alliances formed with new partners are considered exploration.When a firm forms recurrent alliances with a select group of partners,it can rely on existing arrangements and channels to facilitate access and transfer of knowl-edge already prevailing in its immediate alliance network.In this regard,Beckman and colleagues (2004)argued that forming additional alliances with existing partners is a form of exploitation in which a firm reinforces its existing relationships in order to use its current knowledge base.Hence,the proximate network positions of partners facilitates the flow of knowledge and information and en-hances the efficiency of collaboration(Verspagen& Duysters,2004).By forming alliances with familiar partners,firms can also rely on prior experience and interfirm trust to enhance the predictability and reliability of collaboration(Chung,Singh,& Lee,2000;Gulati,1995a;Gulati&Gargiulo,1999; Li&Rowley,2002);such a pattern of alliance for-mation corresponds to March’s(1991)notion of exploitation.In contrast,when partners have no prior ties to a firm,the firm cannot rely on direct experience with these partners,but it can broaden its reach and seek knowledge that cannot be chan-neled through its immediate network.In keeping with March(1991),because a search for partners
TABLE1
Domains of Exploration-Exploitation
Domain Function Structure Attribute
Answers the question What value chain function does
the alliance serve?Whom does the firm partner
with?
To what extent does the partner
differ from prior partners?
Focus Alliance type Network structure Partner profile
Exploration(March,1991) (search,variation,risk
taking,experimentation,
play,flexibility,
discovery,innovation)Forming a knowledge-generating
R&D alliance
Forming an alliance with a
new partner that has no
prior ties to the firm
Forming an alliance with a
partner whose organizational
attributes differ from those of
prior partners
Exploitation(March,1991) (refinement,choice,
production,efficiency,
selection,
implementation,
execution)Forming a knowledge-leveraging
marketing/production alliance
Forming recurrent alliances
with a partner that has
prior ties to the firm
Forming an alliance with a
partner whose organizational
attributes are similar to those
of prior partners
Content of learned knowledge Value chain knowledge such as
new technologies or market
information and expertise in
existing technologies Remote knowledge and
information on partners’
identities and
accessibility or immediate
knowledge and in-depth
familiarity with specific
partners
Exposure to organizational
diversity or specialization in
a specific set of partner
attribute configurations
Relevant references Koza&Lewin(1998);Rothaermel
(2001);Rothaermel&Deeds
(2004)Baum,Rowley,Shipilov,&
Chuang(2005);Beckman,
Haunschild&Phillips
(2004);Verspagen&
Duysters(2004)
Gulati,Lavie,&Singh(2003);
McGrath(2001);Darr&
Kurtzberg(2000)
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beyond a firm’s local network offers new opportu-nities yet greater uncertainty and risk,we concep-tualized it as a form of exploration.
Attribute exploration-exploitation.Unlike the function domain,which defines the nature of alli-ance relationships,and the structure domain, which relates to the prior network positions of part-ners,the attribute domain refers to intertemporal variance in the organizational attributes of a firm’s partners.Following March(1991),we associate exploration with experimentation and variation in routines,processes,technologies,and applications. Exploration enhances adaptation to environmental changes by increasing variance in these organiza-tional attributes(McGrath,2001)and by supporting “long jumps”or reorientations(Levinthal,1997) that enable a firm to adopt new attributes and attain new knowledge outside its domain(Rosenkopf& Nerkar,2001).A deviation from a systematic pat-tern of alliance formation with partners that share certain organizational attributes is thus considered an exploratory behavior.In contrast,when a firm persistently forms new alliances with partners that are similar to its prior partners with respect to attributes such as size and industry focus,it can apply established heuristics and effective gover-nance mechanisms for assimilating external knowl-edge(Darr&Kurtzberg,2000)and can also effi-ciently accumulate and apply its partnering experience in the learning process(Gulati,Lavie,& Singh,2003;Hoang&Rothaermel,2005).Such per-sistence in alliance formation leads to repetition-based improvement,experiential learning,and spe-cialization,which are associated with exploitation (Levinthal&March,1993).Within the attribute do-main,firms’alliance networks range from exhibit-ing consistency in partners’attributes(exploita-tion)to showing frequent deviation from such a pattern(exploration).
The three domains are conceptually distinct,in part,because the content of learned knowledge var-ies across domains(see Table1).Nevertheless,they may be empirically related.
Normative versus Behavioral Perspectives on Balancing Exploration and Exploitation
The notion of balance refers to equilibrium be-tween conflicting tendencies.Existing research re-veals a striking contrast between normative as-sumptions and behavioral tendencies with respect to the balance between exploration and exploita-tion.Prescriptions about whether firms should strive to manage the trade-off between exploration and exploitation are inconsistent with observations about firms’tendencies to balance these activities in actual practice.On the one hand,researchers have normatively assumed that firms should seek to balance exploration and exploitation because both short-term productivity and long-term innova-tion are essential for organizational success and survival(March,1991:87).They have urged firms to pursue both effectiveness and efficiency and to integrate organizational renewal and control, which can be correspondingly enhanced via explo-ration and exploitation.Rivkin and Siggelkow highlighted“the need for an organization to strike the balance between search and stability”(2000: 308),and Siggelkow and Levinthal explicitly re-ferred to the“premise that adaptive entities are charged to maintain a balance of exploration and exploitation”(2003:651).Similarly,Tushman and O’Reilly argued that“organizations can sustain their competitive advantage by operating in multi-ple modes simultaneously—managing for short-term efficiency by emphasizing stability and con-trol,as well as for long-term innovation by taking risks and learning by doing”(1997:167).
On the other hand,despite the undesirable out-comes and self-destructive nature of adaptive pro-cesses(March,1991),failure and success traps may lead to excessive exploration or exploitation,re-sulting in imbalance(Levinthal&March,1993). Thus,in practice,researchers have long recognized the obstacles that firms face when simultaneously pursuing exploration and exploitation,highlight-ing the contradictory natures of activities designed to achieve efficiency and those aimed at flexibility and adaptation(Abernathy,1978).1Firms may seek to overcome these internal organizational trade-offs by engaging in mergers and acquisitions;these ac-tivities yield loosely coupled subunits that are not bound by the same routines and culture as the parent firms and thus maintain buffers between exploratory and exploitative activities.Alliances can also serve as vehicles allowing a firm to explore external opportunities while maintaining an inte-grated internal organization.Nonetheless,empiri-1Organizational research suggests that firms cope with these trade-offs by frequently alternating between incon-sistent organizational designs(Brown&Eisenhardt, 1997),establishing buffers between specialized subunits (Christensen,1998;Levinthal,1997),or maintaining am-bidextrous organizations that integrate these culturally and organizationally differentiated subunits at the corpo-rate level(Benner&Tushman,2003;Tushman& O’Reilly,1997).These ideas are mostly normative be-cause they entail substantial implementation challenges and require empirical validation to determine whether they indeed lead to a balance between exploration and exploitation.
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cal research indicates that exploitation crowds out exploration(Benner&Tushman,2002;Sorenson& Stuart,2001).
In particular,alliance research offers evidence on firms’tendencies to focus on one of these types of activity,explaining what may lead to imbalance, rather than to balance,between exploration and exploitation.The bulk of studies have highlighted exogenous industry forces,such as industry turbu-lence and market uncertainty,that exacerbate firms’tendencies to explore or exploit in their alli-ances(Beckman et al.,2004;Rothaermel,2001b), Even those studies that identify firm characteristics that generate idiosyncratic tendencies to explore or exploit under certain industry conditions(Park et al.,2002;Rothaermel,2001b;Rothaermel&Deeds, 2004)shed almost no light on the organizational mechanisms that guide these tendencies,the trade-offs that they entail,and firms’attempts to balance these tendencies in alliance formation decisions. The balancing of exploration and exploitation in particular domains of alliance formation has thus remained a normative assumption rather than a proven behavioral pattern.In this study,we begin to reconcile the discrepancy between this assump-tion and firms’behavioral tendencies. Conflicting Organizational Pressures for Exploration and Exploitation
In studying whether and how firms balance ex-ploration and exploitation in alliance formation de-cisions,one should consider not only external stimuli in the form of industry conditions but also the internal organizational pressures that guide firms’responses to these stimuli.These fundamen-tal pressures can influence firms’tendencies even in stable industry conditions(Nickerson&Zenger, 2002).In the organizational learning perspective (Levitt&March,1988;March,1991),inertia impels firms toward exploitation,whereas search activi-ties,backed by absorptive capacity,drive explora-tion.The balancing of exploration and exploitation in alliances is challenging given the simultaneous co-existence of these conflicting organizational pressures.
Pressures for exploitation.Pressures for exploi-tation often derive from organizational inertia, which is evident“when the speed of reorganization is much lower than the rate at which environmen-tal conditions change”(Hannan&Freeman,1984; 151).Inertia results from internal forces,such as irreversible managerial commitments and historic decisions,as well as from external forces,such as institutional legitimation(Hannan&Freeman, 1984).Inertia intensifies as established routines and skills become embedded in decision-making processes and are applied almost automatically in response to external stimuli(Nelson&Winter, 1982).When a new problem arises,the firm with inertia engages in local search for relevant experi-ences(Cyert&March,1963;Gavetti&Levinthal, 2000),which yields consistent responses.Hannan and Freeman(1984)noted that inertia elicits ac-countable,reproducible,and reliable organization-al outcomes and thus reduces uncertainty and vari-ability in accordance with March’s(1991)notion of exploitation.In the context of alliances,inertial pressures encourage firms to rely on organizational routines for selecting partners,establishing alliance governance mechanisms,allocating resources,and coordinating and monitoring alliances(Kale,Dyer, &Singh,2002).Hence,inertia may independently inhibit exploration in one or more domains of alli-ance formation.
First,in the function domain,firms that commit to existing technologies(Burgelman,1994;Kelly& Amburgey,1991)are less likely to explore new technologies through their alliances.Accordingly, Rothaermel(2001b)found that incumbents in the pharmaceutical industry benefited by exploiting complementary assets rather than by exploring new technologies with biotechnology partners.Hence, firms may tend to apply their existing knowledge rather than incur the extensive learning costs of knowledge-generating R&D alliances.Inertial pres-sures to reduce technical uncertainty and organiza-tional risk further limit firms’engagements in knowledge-generating alliances because these alli-ances entail substantially more interaction,collab-oration,and exchange of tacit knowledge than do marketing alliances(Rowley et al.,2000).Hence, organizational inertia may facilitate exploitation in that domain.Second,inertia may reduce structure exploration by promoting partner-selection rou-tines that impel firms to enhance the predictability, stability,and reliability of their alliances.Firms can pursue these objectives by forming recurrent alliances with prior partners that are instituted on familiarity,trust,and established collaboration practices(Gulati,1995a).Thus,inertia favors exist-ing partners despite the potential merits of new partners,resulting in structure exploitation.Fi-nally,even when partner selection routines fail to yield relevant partners,firms may still leverage es-tablished routines to identify partners that match a certain profile.In so doing,they specialize and become efficient in managing alliances,thus rein-forcing attribute exploitation.
Pressures for exploration.Whereas inertia drives firms’tendencies to exploit,absorptive ca-pacity facilitates counterpressures by furnishing
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the mechanism via which firms can identify the need for and direction of exploratory activities.Ex-ploration is guided not only by inventing but also by learning from others(Huber,1991;Levitt& March,1988)and by employing external knowl-edge(March&Simon,1958).Absorptive capacity, defined as the ability to value,assimilate,and ap-ply external knowledge(Cohen&Levinthal,1990), helps firms identify emerging opportunities and evaluate their prospects,thus enhancing explora-tion.It adjusts firms’aspiration levels,so that they become attuned to learning opportunities and more proactive in exploring them.Indeed,prior research has demonstrated how absorptive capacity en-hances organizational responsiveness and directs scientific and entrepreneurial discovery(Deeds, 2001;Rosenkopf&Nerkar,2001).It also increases the likelihood of identifying external opportunities and can therefore lead to exploration in one or more domains of alliance formation.
First,absorptive capacity motivates the search for new technologies and the assimilation of exter-nal knowledge,thus facilitating the formation of knowledge-generating R&D alliances.Although ex-ternal knowledge(Huber,1991)can be grafted through corporate acquisitions or employee recruit-ment,R&D alliances offer a cost-efficient and time-sensitive mode of learning(Kumar&Nti,1998). Hence,absorptive capacity leads to function explo-ration.Second,absorptive capacity encourages the pursuit and assimilation of external knowledge and thus motivates firms to identify new partners that can furnish such knowledge.Firms can broaden their knowledge bases by forming alliances with partners with whom they have no prior ties.Fur-ther,absorptive capacity reinforces structure explo-ration since it enhances receptivity to external knowledge and enables firms to apply and internal-ize the knowledge learned from new partners (Mowery,Oxley,&Silverman,1996).For similar reasons,absorptive capacity encourages firms to enrich their knowledge bases by seeking partners that differ from their prior partners with respect to attributes such as size and industry focus under the assumption that these partners offer access to unique knowledge bases and experiences.Thus, absorptive capacity extends the range of partnering opportunities and enables firms to communicate, understand,and collaborate more effectively with a diverse group of partners(Lane,Salk,&Lyles, 2001).Consequently,firms can experiment with new and characteristically different partners.
The challenge of balance.The tension between inertia and absorptive capacity sheds light on the inherent trade-offs between exploration and exploi-tation that prevail within specific domains.These trade-offs emerge not only because of the need to allocate resources for refinement versus develop-ment of technologies or because of the viability of immediate short-term returns versus uncertain long-term returns(March,1991).The challenge of balance in the function,structure,and attribute domains also derives from the fundamentally con-flicting domain-specific pressures imposed by in-ertia and absorptive capacity.Inertia reinforces learning from firms’own experience,but absorp-tive capacity enhances receptivity to external knowledge and thus promotes learning from out-siders(Levitt&March,1988).Whereas absorptive capacity leads to variation,inertia leads to empha-sis on the selection and retention stages of the learning cycle(Zollo&Winter,2002).Unlike ab-sorptive capacity,which generates alternatives and may result in long jumps,inertia compels local search and choice(Gavetti&Levinthal,2000).By investing in absorptive capacity firms attenuate in-ertial forces and constrain their ability to refine and enhance the efficiency of existing routines(March, 1991).As firms develop organizational routines and submit to inertial forces,they subdue their absorptive capacity and adaptability to unfolding environmental events(Hannan&Freeman,1984). Contradicting the normative assumption of bal-ance,we thus expect either exploration or exploi-tation to dominate alliance formation decisions at any given time in specific domains.Two questions remain open:(1)Which activity is likely to domi-nate in each domain?and(2)How can firms bal-ance their exploration and exploitation activities when forming alliances?
Path Dependencies in Exploration and Exploitation within Domains
The tendency to underscore either exploration or exploitation within domains can be ascribed to path dependencies,whereby“a firm’s previous in-vestments and its repertoire of routines(its‘his-tory’)constrain its future behavior”(Teece,Rumelt, Dosi,&Winter,1994:17).Path dependence in ex-ploitation emerges because inertia facilitates rou-tine-based experiential learning.Specifically,a firm’s routines represent persistent patterns of be-havior based on past experience(Nelson&Winter, 1982)that are“the outcome of trial and error learn-ing and the selection and retention of prior behav-iors”(Gavetti&Levinthal,2000:113).Routines that become parts of firms’repertoires are likely to be those that have been previously shown to produce favorable outcomes.In turn,these outcomes may lead to path dependence because the frequency of employing a routine increases its efficiency and the
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likelihood of desirable outcomes,which in turn further reinforce its application(Levinthal& March,1993;Levitt&March,1988).Hence,firms’accumulated exploitation experience reinforces es-tablished routines within each domain.Inertia-driven exploitation is thus likely to intensify with firms’prior exploitation experience.
Absorptive capacity is path dependent as well since the ability to explore new opportunities and evaluate,understand,and acquire new knowledge, depends on firms’past experience in relevant knowledge domains(Zahra&George,2002).The more extensive the scope of firms’prior search activities has been,the more familiar they become with their external environments,and the more effectual their channels and mechanisms for ex-ploring external opportunities become.The broad knowledge base and attention to changing industry conditions and emerging technologies that evolve with absorptive capacity motivate the search for new technologies,experimentation,and learning from external sources(Levitt&March,1988). Therefore,exploration tendencies,guided by ab-sorptive capacity,intensify with firms’prior explo-ration experience.
In the function domain,the leveraging of existing technologies entails nurturing practices for coordi-nating joint marketing engagements,managing in-direct sales,and developing supply chain alliance programs.Such practices typically rely on firms’accumulated experience in function exploitation, whereas experience in R&D alliances may hinder the evolution of these practices because of the dis-crepancy between the natures of downstream and upstream alliances(Rowley et al.,2000).Firms that have concentrated their efforts on forming down-stream alliances are likely to favor these alliances over upstream alliances since this focus allows them to accumulate and apply their experience in a relevant context without encountering significant adjustment costs(Argote&Ophir,2002).Similarly, firms that have previously leveraged their absorp-tive capacity to accumulate experience in manag-ing R&D alliances become more receptive toward external technologies and can establish the com-munication channels,knowledge acquisition,and assimilation procedures needed to further pursue knowledge-generating R&D alliances.Experience in function exploration is therefore self-reinforcing. Similarly,knowledge-sharing routines and rela-tional mechanisms that enhance collaboration and mitigate appropriation hazards in alliances are pri-marily partner-specific(Gulati et al.,2003).There-fore,the benefits arising from firms’past invest-ments in relation-specific assets,trust building, and informal arrangements(Dyer&Singh,1998),while facilitating learning in subsequent alliances with the same partner,cannot be applied as effi-ciently in alliances with other partners.Firms that accumulate experience in recurrent alliances with the same partners thus tend to leverage this expe-rience in structure exploitation.Structure explora-tion,in turn,is path dependent because firms that frequently work with new partners can develop the flexibility,receptivity,and diversity needed for in-teracting with unfamiliar partners and capitalizing on their potentially distinct knowledge bases. Structure exploration experience enhances the ca-pacity of firms to understand new partners and learn from them,whereas firms that concentrate on forming recurrent alliances with the same partners may lack the versatility needed for forming alli-ances with partners who are not already members of their immediate alliance networks.
Finally,the application of partner-selection rou-tines that favor partners who match a certain organ-izational profile becomes more prevalent among firms that have accumulated sufficient experience with prior partners that match that profile.By con-tinuously allying with a homogenous group of part-ners,firms can determine the merits of this prac-tice,and through experiential learning contribute to the evolution of these partner-selection routines (Levinthal&March,1993).In turn,firms that have accumulated experience with a heterogeneous group of partners can develop broad absorptive ca-pacity for interacting and exchanging knowledge with characteristically distinct partners.By over-coming potential epistemological impediments to effective knowledge transfer,these firms are moti-vated to engage in attribute exploration.In sum, exploration and exploitation in alliance formation are self-reinforcing within each domain. Hypothesis 1.Firms encounter path depen-dence in exploration and exploitation within the function,structure,and attribute domains, so that prior experience in exploration(exploi-tation)will reinforce the tendency to explore (exploit)within each domain.
Balancing Exploration and Exploitation
across Domains
Given the conflicting pressures imposed by iner-tia and absorptive capacity,balancing within do-mains is organizationally challenging and entails subduing natural behavioral tendencies and cogni-tive constraints(Levinthal&March,1993).Rather than fully dismissing the normative assumption that firms seek to balance exploration and exploi-tation,we argue that given organizational impedi-
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ments,firms may avoid the inefficiencies that emerge from seeking to reconcile exploration and exploitation within domains by pursuing alterna-tive forms of balance.
In particular,we suggest that firms may balance exploration and exploitation across domains in al-liance formation decisions.Prior research has dem-onstrated that firms can coordinate exploration ef-forts in different areas,such as across technological and organizational boundaries(Rosenkopf& Nerkar,2001)or across technological and geo-graphical domains(Rosenkopf&Almeida,2003). Similarly,in accordance with our distinction among the function,structure,and attribute do-mains in alliance formation,the quest for balance may motivate firms to explore in some of these domains while exploiting in others.For instance, firms may form recurrent R&D alliances(engaging in function exploration)with existing partners(en-gaging in structure exploitation)to leverage famil-iarity and established alliance management rou-tines.Such duality in firms’tendencies is feasible because the pressures of inertia and absorptive ca-pacity within domains may not necessarily conflict across domains.
The organizational trade-offs between explora-tion and exploitation prevail primarily within do-mains,yet firms can simultaneously nurture organ-izational routines that regulate exploitation in one domain while investing in absorptive capacity to support exploration in other domains.For exam-ple,the ability to conduct market research for emerging technologies,develop best practices for learning from partners,and assimilate knowledge in the course of joint R&D alliances does not counter firms’efforts to develop long-term relation-ships,nurture interfirm trust,make relation-specific investments,and use informal governance mechanisms,which are essential in recurrent alli-ances with the same partners(Gulati,1995a).Con-sidering the conflicting pressures imposed by iner-tia and absorptive capacity and firms’inherent tendencies to specialize in either exploration or exploitation within each domain,firms may counter their tendencies to explore in one domain by exploiting in another.
Moreover,firms that simultaneously explore across the three domains may face undesirable and perhaps unnecessary levels of uncertainty and risk. They face technical risk in new technology devel-opment as well as managerial challenges associated with the need to collaborate with unfamiliar or diverse partners.In turn,firms that simultaneously exploit across all domains limit their search activ-ities and constrain potential technical and market opportunities by focusing on the refinement of ex-isting knowledge,fostering only established inter-firm ties,and restraining network heterogeneity, thus limiting long-term prospects.Thus,in view of the need for balance between exploration and ex-ploitation and the behavioral impediments to such balance within domains,we expect firms to exploit in some domains while exploring in others. Hypothesis2.Firms tend to balance explora-tion and exploitation across the function, structure,and attribute domains,so that the tendency to explore(exploit)in one domain will be compensated by the tendency to exploit (explore)in some other domains. Intertemporal Balancing of Exploration and Exploitation within and across Domains
The conflicting pressures of inertia and absorp-tive capacity constrain firms’abilities to simulta-neously balance exploration and exploitation within domains.The self-reinforcing trends as-cribed to prior experience in exploration or exploi-tation further limit firms’abilities to evade these tendencies.We thus expect exploration and exploi-tation trends within domains to be moderate,rather than punctuated or frequently changing(Romanelli &Tushman,1994).Nevertheless,firms may still be able to balance exploration and exploitation by gradually shifting from one learning activity to the other within certain domains.
In so arguing,we follow field research that ex-plains how firms engage in time-paced transitions that enable them to operate in the present while planning and executing future organizational change through sequenced steps(Brown&Eisen-hardt,1997).Our argument is also akin to the no-tion that subtle changes in firms’perceptions of their environments improve sequential attention and adaptation over time(Gavetti&Levinthal, 2000)and that by modulating between discrete or-ganizational choices over time,firms may enjoy temporal efficiency unachievable through either choice alone(Nickerson&Zenger,2002).Hence,in the organizational literature,simulation studies have already demonstrated the merits of intertem-poral sequencing of different organizational struc-tures,suggesting that firms may engage in explora-tion followed by gradual refinement that dislodges them from their current developmental trajectories (Siggelkow&Levinthal,2003).Such practices, therefore,enable firms to avoid competency traps (Levitt&March,1988)and gradually balance ex-ploration and exploitation over time.Stated differ-ently,firms may strive for balance by exploring at a certain point in time and then diligently shifting
804August
Academy of Management Journal
toward exploitation or vice versa.The transition between exploration and exploitation requires firms that have traditionally followed established routines to enhance their absorptive capacity, while firms that have developed expertise in iden-tifying external opportunities and capitalizing on new knowledge must regulate some organizational procedures that improve efficiency.
In the context of alliance formation,firms can balance exploration and exploitation over time by gradually adjusting their tendencies to explore or exploit within each domain.One possible path may involve a gradual shift toward exploitation as firms conclude early R&D efforts and proceed to commer-cialization and production(Rothaermel&Deeds, 2004).Thus,firms initially engage in knowledge-generating R&D alliances and progressively shift to marketing alliances.An alternative path from ex-ploitation to exploration may emerge if firms ex-haust current initiatives and re-engage in techno-logical exploration.Similarly,firms that have engaged in recurrent alliances with a select group of partners may realize that they have fully lever-aged their existing relationships and begin to search for partnering opportunities with new and possibly diverse partners.They can experiment with a small number of new partners without nec-essarily jeopardizing their existing relationships.In turn,firms that have engaged in ad hoc alliances with occasional partners can gradually rationalize their alliance networks and enter recurrent alli-ances with selected partners.For example,Unisys, an information technology firm,quadrupled its number of alliances between1990and1995by forming ad hoc reseller relationships with new partners.Since1995,its number of alliances has remained stable,but Unisys began to engage more extensively in recurrent initiatives,joint activities, and systems integration projects with existing part-ners(Lavie,2004).This pattern illustrates a gradual shift to structure exploitation.
Finally,firms may seek organizationally distinct partners to balance homogeneous networks,or in-stead,begin concentrating on partners that match a certain profile.The transition to attribute explora-tion cannot be consummated instantaneously, however,because an isolated alliance formation event cannot drastically alter the characteristic pro-file of a firm’s prior partners.Additionally,the adjustment of absorptive capacity needed for capi-talizing on such diversity is time-consuming.Thus, the balancing of exploration and exploitation within domains is likely to occur gradually.Tran-sitions within domains may be feasible only over prolonged periods of time because self reinforcing pressures of inertia and absorptive capacity decel-erate them.
Hypothesis3.Firms tend to gradually balance exploration and exploitation within the func-tion,structure,and attribute domains,so that they shift from exploration to exploitation or vice versa over time.
So far we have argued that firms may overcome inherent path dependencies in exploration and ex-ploitation over time within domains.The remain-ing question is which direction such transitions are likely to take.We next posit that the temporal ex-ploration and exploitation trajectories within do-mains are interdependent across domains,so that firms can achieve a balance even when at any given time they face conflicting tendencies within and across domains.
Under the normative assumption that firms seek to balance exploration and exploitation(March, 1991),a shift between exploration and exploitation within a certain domain,even if promoting local equilibrium within that domain,may steer firms away from global equilibrium.Under these circum-stances,firms can compensate for such deviation by countering exploration tendencies in one do-main with exploitation tendencies in another.For example,a firm that shifts its focus from R&D alli-ances to marketing alliances over time may inten-sify its search for new partners and thus balance increasing tendencies to exploit in the function domain with tendencies to explore in the structure domain.The coordination of these trends across domains would enable the firm to conserve its in-vestments in the development of organizational routines and in the nurturing of absorptive capac-ity.Instead of countering inertial forces in one do-main and weakening absorptive capacity in an-other,firms may divert their inertial forces and absorptive capacity from one domain to another to the extent that the corresponding investments and routines are somewhat fungible across domains. For example,firms that have developed informa-tion channels for identifying prospective partners can rely,to an extent,on the same channels for gathering information on the organizational at-tributes of new and existing partners.By simulta-neously balancing exploration and exploitation across domains and over time,firms strive toward an overall balance between exploration and exploitation.
Hypothesis 4.Firms tend to simultaneously balance exploration and exploitation over time and across domains,so that over time,in-creases in the level of exploration(exploita-
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Lavie and Rosenkopf
tion)in one domain will be compensated by decreases in the level of exploration(exploita-tion)in some other domains.
METHODS
Research Setting and Sample
We designed our study as a pooled time series analysis of alliances formed by U.S.software firms. The U.S.software industry(SIC codes7371-7374) offered a suitable setting because intensive alliance formation in this industry enhanced the variance, reliability,and meaningfulness of variables.Also, the high proportion of publicly traded firms made financial information readily available and attenu-ated potential size-and age-related biases.Finally, our sample was representative,since the world-wide software industry has been dominated by United States–based firms.
The study’s time frame spanned the years1990to 2001,although we tracked alliances back to1985 when computing variables such as partnering ex-perience and exploration experience that required information on historic alliances.The five-year window was used under conventional assumptions in alliance research(Stuart,2000).The initial sam-ple of focal firms included all547publicly traded United States–based software firms that were active in2001.Because the analysis was longitudinal,170 firms with less than five years of COMPUSTAT records were discarded.We also eliminated five subsidiaries of other sampled firms and five firms that had no alliances.Because of missing data,the lagging of independent variables,and the require-ment for a minimum number of observations per firm in the computation of some variables,the ef-fective sample size ranged between252and337 firms.Selection bias was ruled out in view of lack of differences between the337sampled firms and the remaining314public firms in the industry.2Data Collection
Following Anand and Khanna(2000b),we first relied on the Securities Data Corporation(SDC) database in compiling records of alliances formed by each focal firm between1985and2001.We then corrected these records by searching alliance an-nouncements and status reports in press releases using the Factiva database,corporate Web sites, and Securities and Exchange Commission(SEC) filings accessed through the Edgar database.Most alliance announcements were cross-validated by at least two sources.By relying on multiple sources and tracking follow-up announcements and status reports,we minimized the occurrence of alliances that were announced but not realized.To further validate our data,we reviewed some of our alliance listings with a select group of corporate executives in charge of alliances.Following these procedures, alliance records were corroborated,corrected, added,or eliminated.For instance,we dropped several resale,licensing,and supply relationships that resembled arm’s-length transactions rather than collaborative alliances.
Overall,we identified19,928alliances involving 8,469unique partners.On average,a focal firm formed58.96alliances between1990and2001. Only24.7percent of the identified alliances were reported in the SDC database.Unlike Anand and Khanna(2000b),we retained the additional records since we employed the firm-year rather than the alliance as the unit of analysis;in our case,elimi-nation of records could have biased measures that entailed complete“ego-network”data.3,4
2The remaining firms included inactive firms,firms with fewer than five years of COMPUSTAT records,and firms headquartered in foreign countries.Insignificant differences were found in total assets(t?1.19,p?.23), revenues(t?0.49,p?.63),number of employees(t?0.01,p?.99),R&D expenses(t?1.02,p?.31),selling, general,and administration expenses(t?1.14,p?.25), net income(t?1.11,p?.27),operating income(t?1.14,p?.25),cash(t?1.57,p?.12),long-term debt(t??0.08,p?.94),earnings per share(t?1.45,p?.15), and other measures.These results suggested that our sample was representative of public firms in the software industry.
3Only72alliances were identified during the years 1985–89,an annual average of0.21alliances per firm; during1990–2001,the average annual number of alli-ances was4.91.This difference in averages reflects the surge in alliance formation during the1990s and the fact that many of the firms in our sample did not commence operations before1990.In fact,only22firms engaged in alliances between1985and1989,thus mitigating con-cerns about potential“left-censoring”in the calculation of partnering experience and structure exploration as a result of exclusion of alliances formed prior to1985.
4When comparing the proportions of different types of alliance agreements in our final sample to those origi-nally reported in SDC,we found that our data offered more extensive coverage of nonequity alliances(t?25.85,p?.001)and alliances with foreign partners(t?25.73,p?.001).The proportions of marketing(t?34.36, p?.001),original equipment manufacturing(OEM)or value-added reseller(VAR)(t?22.89,p?.001),and R&D(t?36.17,p?.001)agreements were also higher in our data than in the SDC data,but the proportions of supply(t??4.16,p?.001),licensing(t??26.87,p?
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Academy of Management Journal
For each alliance,we coded the announcement
date,partners’identities,public status,and agree-
ment types.An alliance could involve more than
one type of agreement.The reliability of our coding
procedure was enhanced by having one of the au-
thors complete all the coding drawing on detailed
guidelines that included alliance definitions,
search techniques,and coding schemes.Interrater
reliability reached 97.8percent when a research
assistant repeated the procedure for a subsample of
six randomly selected firms.Firm-and partner-
specific data,such as annual historical SIC code,
total assets,revenue,long-term debt,R&D ex-
penses,and net income,were extracted from COM-
PUSTAT,which served as a single source for archi-
val data,thus enhancing the reliability of our
measures.The 2,777publicly traded partners in the
sample accounted for 63.6percent of the alliances,
thus limiting potential biases that may have arisen
from the lack of financial information for private
partners.This missing information did not affect
our measures,with the exception of the attribute
exploration variable,which relied on financial in-
formation and could be calculated more accurately
when the proportion of publicly traded partners
was higher.5
We considered the firm-year the unit of analysis
as our dependent variables captured firm-level ten-
dencies.Thus,we transformed the data for the
19,928alliances to 2,451firm-year observations by
pooling the data across all alliances formed by each
focal firm in a given year.The effective sample size
in multivariate analysis ranged between 972and
1,946observations because of the operation-
alization of our measures and missing values.6
Dependent Variables
We operationalized exploration-exploitation
with a combined continuous measure rather than
with two separate indicators under the assumption
that exploration inhibits exploitation and vice
versa,so that these two activities conflict (Abern-
athy,1978;March,1991).This assumption was consistent with the significant,negative correlation that we observed between,for example,upstream and downstream alliance formation in the function domain (r ??.71,p ?.001).Function exploration.We followed Koza and Lewin’s (2000)distinction between exploration,ex-ploitation,and hybrid alliances that integrate downstream and upstream activities.From alliance announcements,we coded a categorical indicator of whether each alliance involved a knowledge-generating R&D agreement (coded 1);an agreement based on existing knowledge involving joint mar-keting and service,OEM/VAR,licensing,produc-tion,or supply (0);or a combination of R&D and other agreements (0.5).Unlike internal R&D that draws directly from a firm’s existing knowledge,R&D agreements in the software industry entail moving outside of the firm’s technical knowledge base or at least integrating internal knowledge with the external knowledge of partners,thus represent-ing exploration.The following is an example of an announcement of an alliance we classified as an R&D agreement:Business Wire.12March 2001—Cadence Design Systems,Inc.and Agere Systems today announced the formation of a strategic alliance to develop chip input/output (I/O)planning capability.This tech-nology alliance will lead to the development of a unique methodology that will promote the co-de-sign of integrated circuits (ICs)and IC packaging to speed time-to-market.Cadence and Agere have teamed to develop this new technology,to help close the gap in the design flow between IC design and IC packaging environments.With its experience in high-speed design,Agere is an excellent ally in the co-development of this new technology.The agreement includes a contractual commitment by Agere to provide Cadence with engineering re-sources for a two-year period.Cadence will deliver to Agere functionality that is based on a jointly-developed product requirement specification.It is worthwhile clarifying that we completed the coding taking the perspective of the focal firm.For example,when a focal firm marketed a solution developed by its partner without engaging in joint R&D efforts,the alliance was coded as a marketing agreement rather than an R&D agreement.Our func-tion exploration measure was calculated as the av-erage value of the alliance agreement indicator across all alliances formed by firm i in year t.Val-ues ranged from 0to 1;high values indicated func-tion exploration,whereas low values indicated function exploitation.Structure exploration.For each alliance formed by firm i ,an indicator received a value of 1if the
.001),and royalties (t ??2.03,p ?.05)agreements were
lower.These results rule out the possibility that the SDC
database covers more substantial types of alliances.
5Compared to private partners,public partners en-
gaged in more strategic long-term alliances (t ?25.61,
p ?.001)and favored joint ventures (t ?6.22,p ?.001)
and R&D alliances (t ?29.69,p ?.001)over marketing
alliances (t ??22,43,p ?.001).
6Missing values occurred,for instance,because SEC
regulations did not require firms to report R&D invest-
ments and because financial information was unavail-
able for privately owned partners.2006807Lavie and Rosenkopf
firm had no joint prior alliances with partner j and
0if such alliances existed.For each firm,structure
exploration was calculated as the average value of
this indicator across all alliances formed by firm i
in year t.In order not to classify a firm’s first alli-
ance as structure exploration by default,we ex-
cluded 181firm-year observations corresponding
to years in which firms formed their first and only
alliances.Auxiliary analysis revealed,however,
that our findings remained unchanged when these
observations were retained.Our findings were also
robust to alternative operationalizations,such as
averaging counts of prior ties as opposed to dummy
indicators.Values again ranged from 0to 1,with
high values indicating structure exploration and
low values,structure exploitation.
Attribute exploration.To enhance construct va-
lidity,we incorporated multiple partner attributes
in our attribute exploration measure.We calculated
four indicators representing distinctive partner at-
tributes in the year of alliance formation,including
partners’size (asset value),propensity to invest in
marketing (advertising intensity),financial strength
(logarithm of the ratio of cash to long-term debt),
and industry focus (four-digit SIC code).For each
alliance,with respect to the first three attributes
(k ?1,2,3),we calculated the absolute difference
between the attribute of the partner and the average
attributes of the ten prior partners of
the firm using
the formula PAD jk ??PA jk ?110?p ?j ?10
j ?1PA pk ?,
where PA jk is the value of attribute k of partner j.
For the partner industry measure (k ?4),we used
a dummy indicator receiving a value of 1when the
primary four-digit SIC code of the new partner was
not included in the list of primary SIC codes of the
ten prior partners of the firm,and 0otherwise.7For
each attribute k,we then calculated the partner attribute difference measure (PAD ikt )as the average PAD jk across all alliances formed by firm i in year t.Since the four PAD ikt measures were not signifi-cantly correlated (average interitem correlation ?.02),we used Euclidian distance rather than factor scores to compute attribute exploration.Before computing this variable,we standardized each PAD ikt measure by subtracting its mean value and dividing the result by its standard deviation.This procedure produces PAD ikt measures that were comparable across attributes.Finally,we applied the Euclidean distance formula ??k ?14sPAD 2ikt to compute the aggregated attribute exploration vari-able for firm i in year https://www.doczj.com/doc/592545638.html,ing linear transformation,we normalized this variable to range between 0and 1,with high values indicating attribute exploration and low values indicating exploitation.8Independent Variables To test Hypothesis 1,we calculated firms’accu-mulated exploration experience within each do-main for each firm-year.We relied on the same formulas used for constructing our exploration measures,but instead of incorporating the alliances formed by firm i in year t,we counted all the alliances formed by that firm between 1985and the preceding year (t ?1).We preferred this measure to such alternatives as one-year lagged exploration variables because we were interested in the overall tendencies of firms to engage in exploration and exploitation over time rather than in their tempo-rary tendencies relative to a preceding year.To study balance across domains (Hypothesis 2),we incorporated simultaneous measures of exploration in alternative domains when testing for exploration tendencies in a given domain.Finally,we mea-sured time on the basis of the year in which alli-ances were formed.For each firm-year,our time 7The restriction to ten prior alliances overcame a po-
tential bias,as the accuracy of measures depended on the
number of prior alliances.The more alliances formed in
the past,the more stable the measure of deviation from
past behavior.Thus,records relating to firms with part-
nering histories comprising fewer than 10alliances were
excluded,and moving averages based on a consistent
partnering history window were calculated for the re-
maining observations.We experimented with different
windows ranging from 5to 15prior alliances,and the
results were robust within this range.The history win-
dow of 10alliances was selected because measures be-
came less stable with shorter history windows,but the
number of omitted observations became substantial with
longer history windows.The choice of this particular
history window was also derived from assumptions
about organizational memory and the adaptation process
based on a firm’s partnering history.Finally,in a supple-mental analysis,we incorporated additional indicators of attribute exploration based on the governance mode and strategic significance of alliances as well as on partners’countries of origin and R&D investments.The findings were consistent but less significant with these alternative measures.8We also considered an alternative measure of at-tribute exploration based on differences between partner attributes and focal firm attributes instead of focusing on differences across partners.This measure produced no significant findings,possibly because firms can engage not only in exploration but also in exploitation by spe-cializing in forming alliances with partners that are or-ganizationally distinct from themselves.
808August Academy of Management Journal
clock ranged between1and12,with1correspond-ing to1990and12corresponding to2001.
Control Variables
Using COMPUSTAT data,we controlled for var-ious time-variant,firm-specific factors that might influence tendencies to engage in exploration and exploitation.Firm size,which has produced conflict-ing impacts on exploration-exploitation in prior stud-ies(Beckroan et al.,2004;Rothaermel&Deeds,2004), was measured as the value of a firm’s assets in a preceding year.Additionally,we controlled for firms’R&D intensity in the preceding year,a variable repre-senting their innovation capacity and internal explo-ration efforts that may affect external exploration ac-tivities through alliances.We controlled for firm age in a preceding year because,as firms mature and become more dependent on their established routines and skills(Hannan&Freeman,1984),they grow less likely to change their strategic orientations(Kelly& Amburgey,1991)and engage in exploration.Simi-larly,we controlled for prior partnering experience, which has been associated with organizational inertia (Li&Rowley,2002)and might account for path de-pendence in alliance formation decisions in the struc-ture domain(Chung et at.,2000;Gulati&Gargiulo, 1999).Prior alliances might also contribute to firms’innovativeness(Ahuja,2000;Tsai,2001)and inter-nalization of partners’capabilities(Mowery et al., 1996),thus enhancing function exploration.Follow-ing prior research(e.g.,Anand&Khanna,2000a;Ho-ang&Rothaermel,2005),for each firm-year we com-puted partnering experience as a count of all prior alliances formed by a focal firm with any partner between1985and the preceding year.
In addition,we controlled for firms’past finan-cial performance,which might reinforce estab-lished routines and drive out exploration (Levinthal&March,1993).Firm profitability,an accounting measure of performance,was based on the ratio of net income to total assets in the preced-ing year.We also controlled for firm solvency,mea-sured with the log-transformed ratio of cash to long-term debt in the preceding year,since the availability of financial funds may facilitate exper-imentation and slack-induced search(Bourgeois, 1981;Levinthal&March,1981).Additionally,we controlled for firms’merger and acquisition activ-ity,following prior research that has identified ac-quisitions as an alternative to alliance formation (Hennart&Reddy,1997;Koza&Balakrishnan, 1993;Villalonga&McGahan,2005).We counted the number of targets that each firm acquired or merged with in a given year,using SDC data.Fi-nally,intertemporal trends were controlled for by including a series of year dummy variables. Analysis
Table2reports descriptive statistics and correla-tions,and Table3reports the results of our analysis of the panel data using cross-sectional time series regressions with random-effects models and gener-alized least square(GLS)estimators.9We ruled out concerns of potential autocorrelation in the data on the basis of the Wooldridge(2002)test,ensuring that our findings were insensitive to the incorpora-tion of first-order autoregressive errors generated from an AR(1)process.Our findings were also ro-bust to the use of maximum-likelihood estimators (MLE)instead of GLS estimators.Variance inflation factors were considerably lower than the critical value,thus ruling out potential multicolinearity. We treated missing values with listwise deletion, which accounts for the variation in model sample sizes.Wald chi-square fit statistics are reported with the results of our GLS models in Table3. For each dependent variable,we report hierar-chical models in Table3.We tested our hypotheses with the full models(4a,4b,and4c),in which the year dummies were replaced with a continuous variable that allowed us to test Hypothesis3.We tested this hypothesis by verifying that the time effect was significant,monotonic,and negative in sign if the predicted level of the dependent variable indicated initial exploration or positive in sign if it indicated initial exploitation.We tested Hypothe-sis4by comparing the valence of the time effects across domains.
RESULTS
Table2reveals low correlations among the depen-dent variables that are consistent with the decompo-sition of the exploration-exploitation construct 9We followed prior research(Beckman et al.,2004; Gulati,1995b;Stuart,1998)in using random-effects mod-els because,unlike these efficient models,fixed-effects models severely reduce degrees of freedom and may gen-erate unstable results for panels over short time periods (our panels included between3.9to5.8observations per firm on average).In addition,fixed-effects models pre-dict annual changes in dependent variables,whereas we were primarily interested in explaining overall explora-tion-exploitation.Moreover,fixed-effects models would have excluded our time variable,as each observation is uniquely identified by a firm-year combination.Hence, the use of fixed-effects models in this study would have severely constrained our analysis.
2006809
Lavie and Rosenkopf
T A B L E 2
D e s c r i p t i v e S t a t i s t i c s a n d C o r r e l a t i o n s
V a r i a b l e s n M e a n s .d .M i n i -m u m M a x i -m u m 12345678910111213
1.F u n c t i o n e x p l o r a t i o n
2,5870.460.35
012.S t r u c t u r e e x p l o r a t i o n
2,4060.890.19
01?.10***3.A t t r i b u t e e x p l o r a t i o n
1,3480.200.1001?.04?.014.F i r m s i z e t ?1
2,2160.381.48
052.15.02?.09***.07*5.F i r m R &D i n t e n s i t y t ?1
1,9650.351.10
021.98?.00.01.07*?.05*6.F i r m a g e t ?1
2,57813.058.29
060?.04??.03?.05.08***?.12***7.P a r t n e r i n g e x p e r i e n c e t ?1
2,58722.2455.3701,301.07***?.22***.08**.53***?.03.11***8.F i r m p r o f i t a b i l i t y t ?1
2,210?0.210.77
?10.076.68.12***?.03?.09***.08***?.25***.17***.07***9.F i r m s o l v e n c y t ?1
2,2044.594.51
?12.0715.42.07***?.11***?.04?.08***.00?.02.19***.13***10.A c q u i s i t i o n s t 2,5870.822.02
044.02?.09***.04.47***?.06**.14***.47***.13***.0211.F u n c t i o n e x p l o r a -t i o n e x p e r i e n c e t ?12,2440.470.2801.28***?.12***?.05?.01.05*?.05*.09***.05*.07**.0212.S t r u c t u r e e x p l o r a -t i o n e x p e r i e n c e t ?12,0700.93
0.09
0.431?.14***.25***?.00?.18***?.02?.03?.42***?.06**?.17***?.16***?.22***13.A t t r i b u t e e x p l o r a -t i o n e x p e r i e n c e t ?11,1400.270.08
01?.11***.02.24***.06?.12***?.02?.00?.07*?.04.05??.24***.11***14.T i m e 2,5877.993.05112?.07***
?.06**.19***.04?.08***.20***.24***?.11***.13***.07***?.11***?.11***.15***?
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to distinctive domains.Specifically,our data dis-prove the premise that the identity of partners(ex-isting versus new)dictates the extent to which they characteristically differ from prior partners.The mean values of the dependent variables indicate tendencies toward structure exploration(y?0.89) and attribute exploitation(y?0.20).
However,exploration and exploitation are rela-tively evenly represented in the function domain (y?0.46).In addition,the high correlations among firm size,acquisitions,and partnering experience suggest that large firms with substantial partnering experience engage more extensively in mergers and acquisitions.Our models reveal overall fit statistics (R2s)ranging between0.04and0.17.However,they are more powerful in explaining variation in explo-ration-exploitation across firms,as reflected in val-ues for R2-between ranging from0.05to0.48. With respect to the control variables,our results suggest that prior partnering experience is associated with exploration in the function domain(??0.08, p?.05)and exploitation in the structure domain (???0.13,p?.001).Supporting Beckman et al. (2004),we found that firms with extensive partnering experience were more likely to seek prior partners for their new alliances.However,experienced firms also tended to engage more extensively in R&D alliances, which entail greater risk,resource commitment,and interaction than marketing alliances(Rowley et al., 2000).Perhaps for similar reasons,function explora-tion was also positively related to profitability(??0.07,p?.05).This finding is consistent with the assertion that resource-poor firms tend to function-ally exploit rather than explore in dynamic markets (Park et al.,2002).
In support of Hypothesis1,model4reveals ten-dencies for imbalance within each domain.Specif-ically,experience in function exploration rein-forces exploration in that domain(??0.29,p?.001);structure exploration experience leads to stronger exploration in the structure domain(??0.20,p?.001);and experience with diverse part-ners—that is,attribute exploration experience—in-creases the tendency to explore in the attribute domain(??0.09,p?.05).These effects persisted even when we controlled for exploration in alter-native domains and were insensitive to the incor-poration of first-order autocorrelation regressors. In keeping with Hypothesis2,we found a nega-tive association between function exploration and simultaneous structure exploration(???0.04,p?.05)and vice versa(???0.08,p?.05).These findings suggest that firms that concentrate on forming R&D alliances also engage in a greater number of alliances with prior partners,whereas those that frequently experiment with new partners favor downstream alliances.10Still,Table3shows
no significant association between function or
structure exploration and tendencies to explore in
the attribute domain.Nevertheless,as Figure1il-
lustrates,firms in our sample tended to compensate
for exploration in the structure domain with ex-
ploitation in the attribute domain.Systematic dif-
ferences were also observed between function and
attribute exploration,suggesting balance across
domains.11
Additionally,in support of Hypothesis3,we
found that firms tended to modify their exploration
tendencies over time irrespective of the reinforcing
influences of exploration experience and the avail-
ability of alternative exploration modes.As the sig-
nificant time effects indicate,function exploitation
increases over time(???0.12,p?.001),while exploration intensifies in the structure(??0.08, p?.05)and attribute(??0.24,p?.001)domains. The time trends in the function and attribute do-
mains are fully consistent with our hypothesis be-
cause they demonstrate a decrease in an initially
high level of exploration in the function domain
(y1990?0.61,??0)and an increase in an initially low level of exploration in the attribute domain
(y1990?0.13,??0).In the structure domain, however,the trend suggests intensifying explora-
tion(See Figure1).12We verified the monotonicity
10We ruled out the alternative explanation that these findings could be fully ascribed to the prevalence of R&D consortia in the software industry that frequently engage the same partners in recurrent R&D alliances.The nega-tive association between activities in the function and structure domains remained significant when we con-trolled for the average number of participants in alliances or excluded multipartner alliances(9.05percent of the announced alliances).
11We verified that the differences in levels of explo-
ration-exploitation across domains were statistically sig-nificant using the Friedman’s distribution-free test for multiple pairwise comparisons.This nonparametric test was appropriate because a Shapiro-Wilk test revealed that our dependent variables violated the normality as-sumption(W?0.99,0.85,0.76,p?.001).We ran this test for subsamples segregated by year in order not to violate the independence assumption.Its results indi-cated differences across all three domains(p?.001). Since this test entailed listwise deletion in unbalanced samples,we also ran the Tukey-Kramer test,which al-lows for unequal sample sizes but assumes a Gaussian distribution.Finally,we verified that our results were robust under the Dunnett T3pairwise comparisons test, for which unequal variances of variables is assumed. These results are available from the authors.
12We ruled out the possibility that the trend in the
structure domain was driven by the increasing popular-
812August
Academy of Management Journal
of the trends in the three domains by introducing
quadratic and cubic terms of the time variable,
which turned out insignificant.13
Finally,the fact that the time effects in model 4
were positive in the structure and attribute do-mains while negative in the function domain sug-gests that,supporting Hypothesis 4,over time firms tend to balance tendencies to explore in one do-main by exploiting in other domains.14In particu-lar,the exacerbated tendency to explore in the structure domain could be understood by consid-ering its balancing effect on intensifying exploita-tion in the function domain (see Figure 1).Hence,the divergence in the direction of intertemporal trends across domains suggested that firms simul-taneously balance exploration and exploitation across domains and over time.DISCUSSION The fertile existing research on exploration-ex-ploitation adopts March’s (1991)balance hypothe-sis but falls short of furnishing empirical evidence that firms indeed conform to this expected behav-ior.Our findings call into question the idea that firms can balance exploration and exploitation within given domains,thus accounting for their ity of alliance formation in the software industry,which
might have accounted for increasing accessibility of new
partners over time,by introducing a control for the an-
nual average number of alliances formed in this industry.
This auxiliary analysis revealed no significant effect of
this popularity measure on structure exploration.We
also verified that the time effects could be ascribed to
firms’tendencies rather than to entry of new firms into
the industry by incorporating an interaction between the
time variable and a dummy moderator indicating
whether a firm was an incumbent that operated before
1990.This interaction was insignificant,but the direct
time effect remained significant.
13We also tested monotonicity by replacing the con-
tinuous time variable with a dummy variable represent-
ing a transition in a specific year.The analysis was re-
peated for transitions in 1990–2000.The transition
coefficients produced for each year had the same valance
in the function domain after 1993(indicating exploita-
tion tendencies);had the same valence in the structure
domain after 1992(exploration tendencies);and had the
same valence throughout the study’s time frame in the
attribute domain (exploration tendencies).Inconsistent
coefficients were insignificant.These results are avail-
able from the authors.14
Consistent results of Friedman and Tukey-Kramer tests for differences across domains in consecutive years offered additional support.These results are available from the authors.FIGURE 1
Intertemporal Trends in Domains of
Exploration-Exploitation
2006813
Lavie and Rosenkopf
conflicting tendencies to explore or exploit in spe-
cific domains of alliance formation (e.g.,Beckman
et al.,2004;Rothaermel &Deeds,2004).We ascribe
these conflicting tendencies to internal pressures of
inertia and absorptive capacity,thus complement-
ing research on exogenous industry conditions that
may drive exploration and exploitation (Koza &
Lewin,1998;Park et al.,2002;Rothaermel,2001;
Rowley et al.,2000).By disentangling distinctive
domains of exploration-exploitation,we reveal
how firms can still balance their exploration and
exploitation tendencies.In fact,the distinctions
among alliance formation domains serve a similar
role to that of the buffers between internal organi-
zational units that presumably support firms’con-
current exploration and exploitation efforts (Ben-
ner &Tushman,2003;Christensen,1998;
Levinthal,1997;Tushman &O’Reilly,1997).We
refute the assumption that firms simultaneously
balance exploration and exploitation within each
domain,yet we show how balance is achieved
across domains and over time.
Our findings are illustrated in Figure 1,which
depicts predicted exploration levels over time
based on model 4while all other variables are held
at their mean levels.The figure suggests that firms
strive to balance exploration and exploitation
within the function domain,resulting in almost
equal proportions of R&D and marketing agree-
ments.They also balance exploration and exploita-
tion across domains,as indicated by the high level
of structure exploration versus the low level of
attribute exploration.Finally,firms balance explo-
ration and exploitation over time,as revealed in the
opposed time trends across domains.Specifically,
as firms proceed from exploration to exploitation in
the function domain,they tend to intensify their
exploration efforts in the structure and attribute
domains.15This process leads to a consistent
midrange level of the compound exploration-ex-
ploitation measure that averages the three domain-
specific measures.
A New Perspective on Balancing Exploration and
Exploitation in Alliances
Our framework suggests that internal pressures
for exploration and exploitation constrain firms’
expected learning behaviors within domains.Nev-
ertheless,firms appear to balance their tendencies
to explore and exploit with respect to the nature of their alliances or choice of partners over time and across domains.For this reason,studies that focus only on one domain are sensitive to the choice of domain and depict only a partial picture of firms’balancing efforts.By spanning a fuller range of domains and longer time frames,scholars can more fully uncover the balance of exploration and ex-ploitation.Although we focused here on alliances,we believe that similar patterns can be observed within organizational boundaries,and we thus ex-tend prior research on the oscillation between or-ganizational forms and the dynamics of explora-tion-exploitation (Brown &Eisenhardt,1997;Nickerson &Zenger,2002;Siggelkow &Levinthal,2003).We acknowledge the challenges associated with the balancing process (Abernathy,1978),noting that the path dependencies that derive from prior exploration-exploitation experience limit firms’abilities to offset the pressures of inertia and ab-sorptive capacity within domains.We identify what may be termed second-order exploitation,whereby firms leverage their experience to enhance the efficiency of either exploration or exploitation activities.Consequently,balancing within domains requires prolonged adjustment to overcome these path dependencies.Accordingly,we advance a dynamic perspective on balance wherein,over time,firms adjust their tendencies to engage in exploration or exploitation within domains.For instance,firms that engage in relatively high proportions of knowledge-generat-ing R&D alliances turn over time to knowledge-leveraging marketing and production alliances.This sequence is consistent with the product devel-opment cycle (Rothaermel &Deeds,2004)in which firms leverage partners’technologies before capital-izing on their market access.In addition,we dem-onstrate that as firms gradually shift from joint R&D to collaborative production and marketing,they tend to experiment with new and diverse partners that can potentially offer a wider range of resources and capabilities.These trends occur independent of the maturation of firms and the entry of new firms into the software industry.Although firms experience path dependencies in exploration-ex-ploitation that hinder their reaction in the short term,gradual adjustment of tendencies within do-mains occurs over time.This adjustment was ap-parent in the function and attribute domains,but in the structure domain path dependencies were too strong to overturn,resulting in intensifying explo-ration.Moreover,we demonstrate that temporal ad-justments in learning activities tend to be traded off across domains.A shift toward exploitation in one
15Perhaps the stronger time trend in the function do-
main relative to the other domains can be attributed to
the initial intermediate level of exploration-exploitation,
which inhibits path dependencies in that domain.814August Academy of Management Journal
domain is accompanied by shifts toward explora-tion in others.
Hence,our study demonstrates how firms simul-taneously balance exploration and exploitation across domains.Indeed,software firms reveal con-flicting tendencies to seek new partners while en-suring that these partners’organizational profiles are quite similar to those of prior partners.This balance across the structure and attribute domains enables firms to access potentially new knowledge bases while reducing the risk of partner unfamiliar-ity(Gulati,1995a)and leveraging prior experience in managing similar alliances.In the same vein,the contrasting tendencies in the function and struc-ture domains further demonstrate how firms avoid the inherent tension between inertia and absorptive capacity by teaming up with“old buddies”when engaging more extensively in highly demanding R&D alliances.The established communication channels,governance mechanisms,and collabora-tion routines available with prior partners support the interactivity,coordination,and resource-sharing needs of these upstream alliances.A bal-ance is maintained because firms that underscore technology development with their R&D alliances tend to be conservative with respect to whom they partner with.No dominant approach for pursuing either exploration or exploitation within domains necessarily exists as long as balance is maintained across domains.Balancing across domains enables firms to become both innovative and efficient in managing alliances while reducing complexity, risk,and uncertainty.
In keeping with March(1991),firms act as adap-tive systems in a state of equilibrium between ex-ploration and exploitation.At any time within a given domain,a firm may emphasize either explo-ration or exploitation,yet across domains and over time,balance is maintained.By recognizing the evolutionary dynamics and multiple facets of ex-ploration and exploitation,our study bridges the gap between the normative assumption that firms should strive to balance exploration and exploita-tion and the observation that in practice firms dem-onstrate polar temporal tendencies to explore or exploit in certain domains.
Limitations and Directions for Future Research Future research could address some of the limi-tations of our study.First,our interorganizational learning perspective could be extended by consid-ering its interplay with intraorganizational learn-ing.The fundamental pressures imposed by inertia and absorptive capacity guide exploration and ex-ploitation not only outside but also inside firm boundaries.Thus,the notion of balancing across domains and over time may apply to intraorganiza-tional learning through,for example,internal de-velopment or mergers and acquisitions.Hence,fu-ture research could uncover the internal domains of exploration and exploitation and study whether and how firms balance exploration and exploita-tion across organizational boundaries.Following the balance hypothesis,we would expect firms that engage in internal exploitation to pursue explora-tion in their alliances.By juxtaposing intra-and interorganizational exploration-exploitation,firms may be able to overcome trade-offs in resource al-location(Cheng&Kesner,1997)and knowledge creation(Rosenkopf&Nerkar,2001)within and across organizational boundaries.
Second,future research might examine various time intervals in assessing temporal adjustments in exploration and exploitation,which could reveal not only path dependencies but also cyclical pat-terns.Longer time intervals should also allow for the incorporation of firm fixed effects,unlike the random-effects models that we used.The more crit-ical question is what drives the time trends that we observed within domains.The balance hypothesis predicts conflicting trends across domains,but within each domain,firms’tendencies may be driven by triggers such as exogenous industry events,corporate leadership changes,or resource allocation constraints(Nickerson&Zenger,2002; Park et al.,2002).A related question is whether the balance we observed results from conscious and proactive strategy(Christensen,1998;Tushman& O’Reilly,1997)or is,rather,a by-product of firms’ad hoc isolated engagements within each domain. Perhaps the relatively modest model fit statistics point to this random component.Field studies could shed more light on the rationale behind this balancing behavior and better isolate managerial discretion from natural evolutionary paths in expli-cating tendencies and transitions.
Third,future research might test our framework in other industries.We focused on the software industry,since its intensity of alliance formation enabled us to effectively track patterns of https://www.doczj.com/doc/592545638.html,anizational pressures in other industries may vary and produce different patterns across domains.Specifically,the software industry is turbulent and thus experiences stronger pres-sures for exploration than stable industries(Rowley et al.,2000).Nonetheless,although firms in other industries may demonstrate different patterns within certain domains,we expect that they would still strive toward balance across domains and over time.
Fourth,future research could overcome some of
2006815
Lavie and Rosenkopf
our empirical limitations by directly measuring in-ertia and absorptive capacity instead of incorporat-ing them as latent mediating constructs.Such a research design might enhance internal validity by, for example,better relating exploration to absorp-tive capacity,as opposed to other intangible assets, which might instead account for embeddedness, heterogeneity,and innovation in alliance networks. Yet direct measurement might require surveys and thus limit researchers’ability to measure and iden-tify time trends.With respect to construct validity, future research might develop alternative operation-alizations of the three domains.For instance,our attribute exploration measure incorporates certain organizational attributes that could be comple-mented with other relevant attributes.In different contexts,certain attributes may be more dominant than others,but scholars should be attuned to data availability constraints,especially with respect to privately held partners.Another avenue for future research would involve the simultaneous analysis of exploration and exploitation at the dyadic level, as a given alliance can be exploratory for one part-ner and exploitative for another.
Finally,future research might elaborate on the performance implications of balancing exploration and exploitation in the context of alliance forma-tion(He&Wong,2004;Rothaermel,2001).Our study confirms the conventional wisdom that firms seek to balance exploration and exploitation (March,1991)but leaves open the question of whether such balance eventually enhances firm performance.Despite its limitations,our study of-fers essential contributions to research on explora-tion and exploitation by demonstrating how firms balance these tendencies over time and across domains.
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816August
Academy of Management Journal
[税务会计工作说明书] 企业税务会计岗位说明书 ××有限公司岗位工作说明书一、岗位标识信息岗位名称： 税务会计隶属部门： 财务部岗位编码： 直接上级： 财务部经理工资等级： 直接下级： 无可轮换岗位：无分析日期： 二、岗位工作概述根据税法和税务程序的规定，负责本公司所有税务的计算及申报工作，按时足额纳税，保障公司的利益和国家权益； 公司的综合统计工作。 三、工作职责与任务（一）负责公司税务的申报 1.进行内销增值税申报； 2.进行外销增值税的免税申报； 3.进行外销增值税退税；
4.进行公司所得税申报； 5.进行个人所得税代扣代缴； 6.进行公司房产税，车船税的申报； 7.负责财政补贴和防洪费的缴纳； 8.进行印花税的计算，贴花及注销。 （二）负责公司进出口业务的核销 1.根据进出口情况核销进出口业务； 2.领取进出口所需的业务单据。 （三）协助人事部进行劳动工资的计算 1.与人事部合作，计算公司员工的工资奖金、加班费及各种保险基金； 2.在规定的时间里发放各项工资。 （四）向上级有关部门报送相应的报表 1.填写、录入公司各财务报表； 2.向税务、财政报送季度资产负债表、利润表及年度全套报表等； 3.填制对外统计台账和月度报表；
4.向上级主管单位送交统计报表或财务报表。 （五）完成上级委派的其他任务四、工作绩效标准（一）按时足额纳税，保证税务申报及时准确，减少公司不必要的损失； （二）准确核销进出口业务，保证进出口业务的顺利进行； （三）准确计算劳动工资； （四）按时向上级报送报表。 五、岗位工作关系（一）内部关系 1.所受监督：在税务的申报和税款的缴纳方面，直接接受财务部经理的指示和监督； 2.所施监督：一般情况本岗位不实施对其他岗位的工作监督； 3.合作关系：在进出口核销方面，向销售部取得相关的内销外销发票，在协助核算劳资方面，向人事部取得工资清单。 （二）外部关系在进行税务申报方面，与税务局发生联系，在进出口核销方面，与外汇管理局发生联系，在申报缴纳地税方面，与财政局发生联系，在缴纳税款方面，与银行发生联系。 六、岗位工作权限（一）对进出口业务的审核权； （二）税款的缴纳权；
脐带间充质干细胞的研究进展 间充质干细胞（mesenchymal stem cells,MSC S ）是来源于发育早期中胚层 的一类多能干细胞[1-5]，MSC S 由于它的自我更新和多项分化潜能，而具有巨大的 治疗价值 ,日益受到关注。MSC S 有以下特点：(1)多向分化潜能，在适当的诱导条件下可分化为肌细胞[2]、成骨细胞[3、4]、脂肪细胞、神经细胞[9]、肝细胞[6]、心肌细胞[10]和表皮细胞[11, 12]；(2)通过分泌可溶性因子和转分化促进创面愈合；(3) 免疫调控功能，骨髓源（bone marrow ）MSC S 表达MHC-I类分子，不表达MHC-II 类分子，不表达CD80、CD86、CD40等协同刺激分子，体外抑制混合淋巴细胞反应，体内诱导免疫耐受[11, 15]，在预防和治疗移植物抗宿主病、诱导器官移植免疫耐受等领域有较好的应用前景；(4)连续传代培养和冷冻保存后仍具有多向分化潜能，可作为理想的种子细胞用于组织工程和细胞替代治疗。1974年Friedenstein [16] 首先证明了骨髓中存在MSC S ，以后的研究证明MSC S 不仅存在于骨髓中，也存在 于其他一些组织与器官的间质中：如外周血[17]，脐血[5]，松质骨[1, 18]，脂肪组织[1]，滑膜[18]和脐带。在所有这些来源中，脐血(umbilical cord blood)和脐带(umbilical cord)是MSC S 最理想的来源，因为它们可以通过非侵入性手段容易获 得，并且病毒污染的风险低，还可冷冻保存后行自体移植。然而，脐血MSC的培养成功率不高[19, 23-24]，Shetty 的研究认为只有6%，而脐带MSC的培养成功率可 达100%[25]。另外从脐血中分离MSC S ，就浪费了其中的造血干/祖细胞(hematopoietic stem cells/hematopoietic progenitor cells,HSCs/HPCs) [26, 27]，因此，脐带MSC S (umbilical cord mesenchymal stem cells, UC-MSC S )就成 为重要来源。 一．概述 人脐带约40 g, 它的长度约60–65 cm, 足月脐带的平均直径约1.5 cm[28, 29]。脐带被覆着鳞状上皮，叫脐带上皮，是单层或复层结构，这层上皮由羊膜延续过来[30, 31]。脐带的内部是两根动脉和一根静脉，血管之间是粘液样的结缔组织，叫做沃顿胶质，充当血管外膜的功能。脐带中无毛细血管和淋巴系统。沃顿胶质的网状系统是糖蛋白微纤维和胶原纤维。沃顿胶质中最多的葡萄糖胺聚糖是透明质酸，它是包绕在成纤维样细胞和胶原纤维周围的并维持脐带形状的水合凝胶，使脐带免受挤压。沃顿胶质的基质细胞是成纤维样细胞[32]，这种中间丝蛋白表达于间充质来源的细胞如成纤维细胞的，而不表达于平滑肌细胞。共表达波形蛋白和索蛋白提示这些细胞本质上肌纤维母细胞。 脐带基质细胞也是一种具有多能干细胞特点的细胞，具有多项分化潜能，其 形态和生物学特点与骨髓源性MSC S 相似[5, 20, 21, 38, 46]，但脐带MSC S 更原始，是介 于成体干细胞和胚胎干细胞之间的一种干细胞，表达Oct-4, Sox-2和Nanog等多
浅析资产重组中的财务处理 [摘要] 文章由国企改革谈起，从财务的角度分析了资产重组的内涵，针对当前国有企业的重组、改制提出了一些有意义的见解。 改革开放以来，我国在推进国有经济布局和结构调整方面取得了重大进展，过去国有经济布局覆盖过宽、分布过广，现在则按市场方向有进有退，使国有经济在市场经济充分发挥作用的地区和领域逐步退出，并集中于更有利于发挥作用的领域。我国深化经济体制改革的总体要求是“完善社会主义市场经济体制，推动经济结构战略性调整”，重点是“坚持和完善差不多经济制度，深化国有资产治理体制改革”。也确实是讲，现时期的国有资产治理体制改革即是一场深刻的体制革命，也是国有经济结构重大调整过程，作为这一改革的重要实现形式，确实是国有企业的大规模重组。本文从财务会计的角度对资产重组这一课题作了一些分析并提出一些有意义的建议。 一、资产重组的含义 （一）概念
资产重组是指通过不同法人主体的法人财产权、出资人所有权及债权人债权进行符合资本最大增值目的的相互调整与改变，对实业资本、金融资本、产权资本和无形资本的重新组合。重组是企业为了实现一定的目标即猎取利润及股东投资回报率最大化，充分使用治理和资源以及应付日益激烈的市场竞争。重组会引起资产或资本以及治理策略的改变。 （二）分类 资产重组通常涉及：资产注入，资产或业务的出售，资产重新的整合，债务、资本比率的改变，新形式的资本、债务形式，借款期的改变等。 重组能够以多种形式进行，包括：资产注入、兼并、股份化、破产、出售、建立核心子公司等。既然资产重组能够为不同企业提供较多可选择模式，也确实是我们在采纳重组形式中有了更多的回旋余地。具体包括以下几种模式： 1.所有权换位的资产重组，即资产的所有权在不同的的产权主体之间发生转换或实现重新组合。如注入新资产、兼并、合并、收购。许多
精神分裂症的病因及发病机理 精神分裂症病因：尚未明，近百年来的研究结果也仅发现一些可能的致病因素。（一）生物学因素1．遗传遗传因素是精神分裂症最可能的一种素质因素。国内家系调查资料表明：精神分裂症患者亲属中的患病率比一般居民高6.2倍，血缘关系愈近，患病率也愈高。双生子研究表明：遗传信息几乎相同的单卵双生子的同病率远较遗传信息不完全相同 的双卵双生子为高，综合近年来11项研究资料：单卵双生子同病率（56.7%），是双卵双生子同病率（12.7%）的4.5倍，是一般人口患难与共病率的35-60倍。说明遗传因素在本病发生中具有重要作用，寄养子研究也证明遗传因素是本症发病的主要因素，而环境因素的重要性较小。以往的研究证明疾病并不按类型进行遗传，目前认为多基因遗传方式的可能性最大，也有人认为是常染色体单基因遗传或多源性遗传。Shields发现病情愈轻，病因愈复杂，愈属多源性遗传。高发家系的前瞻性研究与分子遗传的研究相结合，可能阐明一些问题。国内有报道用人类原癌基因Ha-ras-1为探针，对精神病患者基因组进行限止性片段长度多态性的分析，结果提示11号染色体上可能存在着精神分裂症与双相情感性精神病有关的DNA序列。2．性格特征：约40%患者的病前性格具有孤僻、冷淡、敏感、多疑、富于幻想等特征，即内向
型性格。3．其它：精神分裂症发病与年龄有一定关系，多发生于青壮年，约1/2患者于20～30岁发病。发病年龄与临床类型有关，偏执型发病较晚，有资料提示偏执型平均发病年龄为35岁，其它型为23岁。80年代国内12地区调查资料：女性总患病率（7.07%。）与时点患病率（5.91%。）明显高于男性（4.33%。与3.68%。）。Kretschmer在描述性格与精神分裂症关系时指出：61%患者为瘦长型和运动家型，12.8%为肥胖型，11.3%发育不良型。在躯体疾病或分娩之后发生精神分裂症是很常见的现象，可能是心理性生理性应激的非特异性影响。部分患者在脑外伤后或感染性疾病后发病；有报告在精神分裂症患者的脑脊液中发现病毒性物质；月经期内病情加重等躯体因素都可能是诱发因素，但在精神分裂症发病机理中的价值有待进一步证实。（二）心理社会因素1．环境因素①家庭中父母的性格，言行、举止和教育方式（如放纵、溺爱、过严）等都会影响子女的心身健康或导致个性偏离常态。②家庭成员间的关系及其精神交流的紊乱。③生活不安定、居住拥挤、职业不固定、人际关系不良、噪音干扰、环境污染等均对发病有一定作用。农村精神分裂症发病率明显低于城市。2．心理因素一般认为生活事件可发诱发精神分裂症。诸如失学、失恋、学习紧张、家庭纠纷、夫妻不和、意处事故等均对发病有一定影响，但这些事件的性质均无特殊性。因此，心理因素也仅属诱发因
税务会计的岗位职责 责任心使我们约束自己，完善自己所必需的，它将伴你成长。下面是小编整理的税务会计岗位职责，供你参考，希望能对你有所帮助。 【第1篇】税务会计岗位职责 1、专业人员职位，在上级的领导和监督下定期完成量化的工作要求，并能独立处理和解决所负责的任务; 2、独立办理税务外经证、开票等税务相关工作，能独立办理企业税务上面的交纳、复核工作。 3、办理有关的交纳、完税申请及退税冲账等事项 4、编制有关税务报表及相关分析报告。负责增值税发票的申请统计和公司进项抵扣发票票源组织，依据进项和销项以及公司开票管理的规定合理开据发票，申报纳税。 5、解答各项税务等相关问题 6、协助财务经理完成一些事务性工作，完成领导交办的其它工作任务 【第2篇】税务会计岗位职责 1、协助财务经理和会计开展工作，做好会计核算和分析。 2、负责日常记账凭证的录入。 3、负责定期核对现金、银行存款，做好现金盘点表及银行存款余额调节表。 4、认真核对、整理各项收支原始单据，凡未按规定审批或违反财经制度单据，一律不得入账。 5、负责发票的购买、开具，确保发票的正常供应和开具的发票内容真实完整、金额准确无误。 6、办理其他有关的财会事务，做好文书及日常事务工作。 7、负责会计档案的整理、装订。 8、完成领导交办的其他工作。 【第3篇】税务会计岗位职责 1、统筹负责发票领购、保管、开具，月末扫描、认证，按规定及时登记发票领购簿;
2、管理规范涉税事项，发现问题及时反馈，规避公司涉税风险，填制税务及统计报表; 3、按时完成月度报税工作，依法合规纳税，协助财务经理完成年报工作; 4、每月对纳税申报、税负情况进行综合分析，提出合理化建议; 5、收集各类税务法规、制度，定期对财务人员进行税务培训; 【第4篇】税务会计岗位职责 1.根据国家财务会计法规和行业会计规定，结合公司特点，负责拟订公司税务会计核算的有关工作细则和具本规定，报经领导批准后实施。 2.根据国家会计法规规定，准确、及时地做好账务和结算工作，正确进行会计核算，填制和审核会计凭证，登记明细账和总账。 3.负责编制公司月度、年度会计报表。 4.负责公司税金的计算、申报和清缴工作，协助有关部门开展财务审计和年检。 5.负责会计监督。根据规定的成本、费用开支范围和标准，审核原始凭证的合法性、合理性和真实性，审核费用审批手续是否符合公司规定。 6.及时做好会计凭证、账册、报表等财会资料的收集、汇编、归档等会计档案管理工作。 【第5篇】税务会计岗位职责 1.增值税专用发票抵扣及验旧 2.通过SAP软件对财务相关数据进行汇总、整理、分析 3.月末税金结转等相关结账工作 4.负责编制国税、地税需要的各种报表。 5.按月及时办理国、地税纳税申报并缴纳各项税种，编制相关会计凭证，按年完成年度审计及汇算清缴工作; 6.负责办理地税、国税年度年检工作; 7.配合财政、税务、审计等部门的检查，如实提供检查所需各项财务资料。 8.办理其他与税务有关的事项及主管安排的其他工作。
脐带血造血干细胞库管理办法（试行） 第一章总则 第一条为合理利用我国脐带血造血干细胞资源，促进脐带血造血干细胞移植高新技术的发展，确保脐带血 造血干细胞应用的安全性和有效性，特制定本管理办法。 第二条脐带血造血干细胞库是指以人体造血干细胞移植为目的，具有采集、处理、保存和提供造血干细胞 的能力，并具有相当研究实力的特殊血站。 任何单位和个人不得以营利为目的进行脐带血采供活动。 第三条本办法所指脐带血为与孕妇和新生儿血容量和血循环无关的，由新生儿脐带扎断后的远端所采集的 胎盘血。 第四条对脐带血造血干细胞库实行全国统一规划，统一布局，统一标准，统一规范和统一管理制度。 第二章设置审批 第五条国务院卫生行政部门根据我国人口分布、卫生资源、临床造血干细胞移植需要等实际情况，制订我 国脐带血造血干细胞库设置的总体布局和发展规划。 第六条脐带血造血干细胞库的设置必须经国务院卫生行政部门批准。 第七条国务院卫生行政部门成立由有关方面专家组成的脐带血造血干细胞库专家委员会（以下简称专家委
员会），负责对脐带血造血干细胞库设置的申请、验收和考评提出论证意见。专家委员会负责制订脐带血 造血干细胞库建设、操作、运行等技术标准。 第八条脐带血造血干细胞库设置的申请者除符合国家规划和布局要求，具备设置一般血站基本条件之外， 还需具备下列条件： （一）具有基本的血液学研究基础和造血干细胞研究能力； （二）具有符合储存不低于1 万份脐带血的高清洁度的空间和冷冻设备的设计规划； （三）具有血细胞生物学、HLA 配型、相关病原体检测、遗传学和冷冻生物学、专供脐带血处理等符合GMP、 GLP 标准的实验室、资料保存室； （四）具有流式细胞仪、程控冷冻仪、PCR 仪和细胞冷冻及相关检测及计算机网络管理等仪器设备； （五）具有独立开展实验血液学、免疫学、造血细胞培养、检测、HLA 配型、病原体检测、冷冻生物学、 管理、质量控制和监测、仪器操作、资料保管和共享等方面的技术、管理和服务人员； （六）具有安全可靠的脐带血来源保证； （七）具备多渠道筹集建设资金运转经费的能力。 第九条设置脐带血造血干细胞库应向所在地省级卫生行政部门提交设置可行性研究报告，内容包括：
一、企业资产的两次重组模式资产重组已成为时下我国证券市场中使用最为频繁的术语之一，但实际上，各方面对资产重组的理解却不统一。在一些著述中，资产重组常常同所谓的“资产经营”、“资本运营”或是“资本重组”等概念混淆。在西方经济学和管理学著作中，常见的说法是“reorganizition”或者是“restructure”，这实际上是指企业内部的资产重整过程，不涉及公司控制权的变更，同我国所谓的“资产重组”并不一样。与目前我国上市公司的“资产重组”这一提法相近的概念有两个，一是并购，即兼并收购（M&A）；另一个是资产经营。这两个概念都是指公司间涉及资产项目变更的经营行为，但不同的是，兼并和收购一般指影响产权变更的资产变动，而资产经营应该是指公司为了控制所控资产的风险和预期收益，调整证券资产和实物资产组合从而分散投资风险。提高投资收益的行为。一般来说，资产经营并不涉及产权的变更。在中国证券市场上，“资产重组”这一概念的涵概并不是很清楚，而是兼并、收购、托管、资产置换、借壳，买壳等行为的总称。实际上，上市公司资产重组的内容早已超越了资产的范畴，如国有股的无偿划拨、无资产注入的公司控制权的变化以及债务重组等。可见，我国证券市场所常用的“资产重组”不是一个边界较为分明的概念，而是已被市场约定俗成为一个边界模糊的、表述一切有关上市公司重大非经营性或正常性变化的总称。我国上市公司的资产重组活动是我国在市场经济转轨过程中的一种较为独特的现象，是在我国证券市场发育尚不完善，证券发行机制、上市公司产业结构和股权结构不合理的条件下的一种市场主体和市场本身重新调整的过程。因此，一般来说，资产重组概念可作如下归纳；所谓资产重组，就是通过兼并、收购、合并、出售等方式，实现资产主体的重新选择和组合，优化企业资产结构，提高企业资产的总体质量，最终建立起符合市场经济要求的、更富有竞争力的资产组织体系。上市公司资产重组是一个内涵和外延都较宽泛的概念。从内涵上看，它是指以上市公司为主体而从事的各种资产重组。从外延上看，上市公司资产重组既包括公司上市前的资产重组（股份制改组式的资产重组），又包括企业上市后的资产重组；既包括上市公司之间的兼并和收购，又包括上市公司兼并收购非上市公司以及非上市公司并购上市公司；既包括国有企业海外上市，又包括外资并购中国的国有企业。一般来说，上市司资产重组的模式可以分为初次重组模式和再次重组模式。初次重组是企业为了向社会募集股份并上市交易，通过合并、分离等资产重组方式，调整股东权益和财务组织结构，以达到有关法律法规和证券监管机构的要求的过程。申请上市的企业在上市前，对企业结构的重组常常采用以下一种或多种资产重组模式进行：（1）整体改组上市模式；（2）合并改组上市模式：（3）整体改组分立模式；（4）部分改组分立模式；（5）共同重组模式；（6）买壳上市模式；（7）借壳上市模式。企业在上市后，为达到优化资源配置，发挥资本最大效益的经营目的，需要实施进一步重组，从而向最优的资产结构和组织形式靠拢。这种再次重组的过程是对上市公司以上市为目的初次重组的深化。从某种意义上说，公司上市以后进行的再次重组才是真正意义上的符合市场规则的资产重组，一般来说其效率与效果也较初次重组好得多。近年来，伴随着上市公司并购和资产重组热的兴起，上市公司再次重组的模式也不断推陈出新，归纳起来，大体有资产剥离、兼并收购、合并重组、资产托管等几种主要模式。[!--empirenews.page--] 二、初次重组中财务会计问题的处理（一）关于基本会计报表基本会计报表是指改制企业在资产重组过程中编制的，反映其前三年财务状况、经营成果和资金变动情况的会计报表。一般来说，拟上市企业只有在股份公司正式成立后才形成真正的会计主体，但为了反映它前三年的经营业绩，通常都假设按资产重组方案改制后设立的股份公司在前三年已经存在并持续经营，以此编制前三年及最近一期的会计报表。但是，基本会计报表的主体只是虚拟的，它从未正式存在过。如果企业是整体改组，原核算主体单一，不存在复杂的投资控股关系，则可编制较为简单的基本会计报表；但如果企业采用共同改组或分立式改组模式，涉及大范围的资产重组，或原企业核算主体较多和存在复杂的投资控股关系，那么基本会计报表应按那一种组织架构编制还有待
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浅析资产重组中的财务处理 [摘要] 文章由国企改革谈起，从财务的角度分析了资产重组的内涵，针对当前国有企业的重组、改制提出了一些有意义的见解。 改革开放以来，我国在推进国有经济布局和结构调整方面取得了重大进展，过去国有经济布局覆盖过宽、分布过广，现在则按市场方向有进有退，使国有经济在市场经济充分发挥作用的地区和领域逐步退出，并集中于更有利于发挥作用的领域。我国深化经济体制改革的总体要求是“完善社会主义市场经济体制，推动经济结构战略性调整”，重点是“坚持和完善基本经济制度，深化国有资产管理体制改革”。也就是说，现阶段的国有资产管理体制改革即是一场深刻的体制革命，也是国有经济结构重大调整过程，作为这一改革的重要实现形式，就是国有企业的大规模重组。本文从财务会计的角度对资产重组这一课题作了一些分析并提出一些有意义的建议。 一、资产重组的含义 （一）概念 资产重组是指通过不同法人主体的法人财产权、出资人所有权及债权人债权进行符合资本最大增值目的的相互调整与改变，对实业资本、金融资本、产权资本和无形资本的重新组合。重组是企业为了实现一定的目标即获取利润及股东投资回报率最大化，充分使用管理和资源以及对付日益激烈的市场竞争。重组会引起资产或资本以及管理策略的改变。 （二）分类 资产重组通常涉及：资产注入，资产或业务的出售，资产重新的整合，债务、资本比率的改变，新形式的资本、债务形式，借款期的改变等。
重组可以以多种形式进行，包括：资产注入、兼并、股份化、破产、出售、建立核心子公司等。既然资产重组可以为不同企业提供较多可选择模式，也就是我们在采用重组形式中有了更多的回旋余地。具体包括以下几种模式： 1.所有权换位的资产重组，即资产的所有权在不同的的产权主体之间发生转换或实现重新组合。如注入新资产、兼并、合并、收购。许多西方国家的公司就是通过收购取得对企业的所有权来扩大实力。这种重组方式也越来越多地被我国的上市公司所采用。 2.非所有权换位的资产重组，即资产的最终所有权不变，仅仅是资产的使用权、收益权、处置权、让渡权在不同的资产主体之间发生转换或实现重新组合。 3.根据市场法则进行的资产重组，即遵循市场经济法则，通过市场的公平交易将资产的所有权在不同的产权主体之间实现重新组合，如资产拍卖、证券市场的合法收购等。 4.非市场型资产重组，即利用行政及法律等超经济力，可不按市场经济法则，通过强制力将资产的所有权在不同的产权主体之间实现转化或重新组合。 综上所述，我国现在所要进行的资产重组属于非所有权、非市场型资产重组。也就是说这种资产重组是通过国家强制力量实现的，而非市场运作，带有很浓重的行政色彩。 （三）原则 根据国有企业的具体情况，在企业资产重组工作中应遵循以下几个基本原则。 1.规范国家与企业的关系。 2.合理经营资产，健全生产经营体系。首先是要通过必要的企业资产重组，使经营资产重新组合，集中原企业或企业集团中最有竞争力的主要业务，体现专业化经营水平。 其次，要通过资产重组使公司自身形成健全的生产经营体系。
精神分裂症的发病原因是什么 精神分裂症是一种精神病，对于我们的影响是很大的，如果不幸患上就要及时做好治疗，不然后果会很严重，无法进行正常的工作和生活，是一件很尴尬的事情。因此为了避免患上这样的疾病，我们就要做好预防，今天我们就请广州协佳的专家张可斌来介绍一下精神分裂症的发病原因。 精神分裂症是严重影响人们身体健康的一种疾病，这种疾病会让我们整体看起来不正常，会出现胡言乱语的情况，甚至还会出现幻想幻听，可见精神分裂症这种病的危害程度。 (1)精神刺激：人的心理与社会因素密切相关，个人与社会环境不相适应，就产生了精神刺激，精神刺激导致大脑功能紊乱，出现精神障碍。不管是令人愉快的良性刺激，还是使人痛苦的恶性刺激，超过一定的限度都会对人的心理造成影响。 (2)遗传因素：精神病中如精神分裂症、情感性精神障碍，家族中精神病的患病率明显高于一般普通人群，而且血缘关系愈近，发病机会愈高。此外，精神发育迟滞、癫痫性精神障碍的遗传性在发病因素中也占相当的比重。这也是精神病的病因之一。 (3)自身：在同样的环境中，承受同样的精神刺激，那些心理素质差、对精神刺激耐受力低的人易发病。通常情况下，性格内向、心胸狭窄、过分自尊的人，不与人交往、孤僻懒散的人受挫折后容易出现精神异常。 (4)躯体因素：感染、中毒、颅脑外伤、肿瘤、内分泌、代谢及营养障碍等均可导致精神障碍，。但应注意，精神障碍伴有的躯体因素，并不完全与精神症状直接相关，有些是由躯体因素直接引起的，有些则是以躯体因素只作为一种诱因而存在。 孕期感染。如果在怀孕期间，孕妇感染了某种病毒，病毒也传染给了胎儿的话，那么，胎儿出生长大后患上精神分裂症的可能性是极其的大。所以怀孕中的女性朋友要注意卫生，尽量不要接触病毒源。 上述就是关于精神分裂症的发病原因，想必大家都已经知道了吧。患上精神分裂症之后，大家也不必过于伤心，现在我国的医疗水平是足以让大家快速恢复过来的，所以说一定要保持良好的情绪。
税务会计岗位职责及工作细则 岗位职责： 对外账的合理性、合法性负全责。 1、严格按照国家税法规定对公司财务进行账务处理及纳税申报。 2、每月10日前编制地税（城建税、教育费附加、个人所得税、印花税、工会经费等）、国税纳税申报表，负责在规定时间内按时缴纳各种地方税费及纳税申报，遇节假日顺延。 3、负责日常开具各种增值税发票、普通发票、个体业发票及其他与税务相关的票据。 4、负责及时购买国税普票、增值税发票及个体业发票。 5、负责空白发票、未认证进项发票及已开出销项发票的登记管理，经常开发票客户的要按客户立账页进行管理，每月只开两次以内的客户集中管理，要对发票开出的合理性、真实性负责。 6、负责继发伟业、万邦日常对税业务凭证的财务软件录入及继发恒信对税业务凭证的手工编制、账簿登记。 7、负责继发伟业、继发恒信、万邦的银行对账单核对。做到财务账与银行对账单账单相符。 工作细则： 一、开具发票 开发票总原则：对税财务账上有库存或是有库存可补时方可开具销项发票，不允许出现负库存。 1、有开具发票申请时要对开发票申请单进行审核，审核内容如下
1）开具发票申请单是否按项填写清晰。 2）根据申请单上的管家婆单位名称在管家婆软件中核查实际销售时是否为带票销售，不带票销售在开发票时要加收税点，由客户将税点汇到账上后再开具发票；或填写挂税点单据由业务员签字、总经理签字，可先开具此发票，总经理后补签字。挂税点单据要及时录入管家婆账目中。 个体发票加5%个税点，增票8%个税点，所开发票品项没有进项又要求对项开发票的，而且公司原账上库存也没有进项可补需开个体发票补进项的加22%个税点。 开发票时不要求对项的实际开发票时要开账上库存较多且开对项发票时及少涉及的品项或是开具进项发票可以不对项开的厂家的品项。 要求对项开发票的，要遵守公司有进项可补，无进项可补经总经理同意方可开具发票，同时要审核无进项可补带票销售的是按基本利润另加22%个税点。 3）要审核开具发票的金额是否与管家婆中该客户的销售金额一致或小于管家婆中该客户的销售金额，超过管家婆中该客户的实际销售金额1000以上的要经总经理同意，超过金额要加收8%个税点。写明回款金额的要进行核对。 2、开销售单时是不带票销售的，后期如果客户再要求开发票，财务只能不对项开。 3、原则上销售金额不够一万的客户要开具发票，要攒够一万再开发
企业资产两次重组中财务会计问题的处理研究 一、企业资产的两次重组模式 资产重组已成为时下我国中使用最为频繁的术语之一，但实际上，各方面对资产重组的理解却不统一。在一些著述中，资产重组常常同所谓的“资产经营”、“资本运营”或是“资本重组”等概念混淆。在西方学和管著作中，常见的说法是“reorganizition”或者是“restructure”，这实际上是指企业内部的资产重整过程，不涉及公司控制权的变更，同我国所谓的“资产重组”并不一样。与目前我国的“资产重组”这一提法相近的概念有两个，一是并购，即兼并收购（M&A）；另一个是资产经营。这两个概念都是指公司间涉及资产项目变更的经营行为，但不同的是，兼并和收购一般指影响产权变更的资产变动，而资产经营应该是指公司为了控制所控资产的风险和预期收益，调整证券资产和实物资产组合从而分散风险。提高投资收益的行为。一般来说，资产经营并不涉及产权的变更。在中国证券市场上，“资产重组”这一概念的涵概并不是很清楚，而是兼并、收购、托管、资产置换、借壳，买壳等行为的总称。实际上，上市公司资产重组的内容早已超越了资产的范畴，如国有股的无偿划拨、无资产注入的公司控制权的变化以及重组等。可见，我国证券市场所常用的“资产重组”不是一个边界较为分明的概念，而是已被市场约定俗成为一个边界模糊的、表述一切有关上市公司重大非经营性或正常性变化的总称。
我国上市公司的资产重组活动是我国在市场经济转轨过程中的一种较为独特的现象，是在我国证券市场发育尚不完善，证券发行机制、上市公司产业结构和股权结构不合理的条件下的一种市场主体和市场本身重新调整的过程。因此，一般来说，资产重组概念可作如下归纳；所谓资产重组，就是通过兼并、收购、合并、出售等方式，实现资产主体的重新选择和组合，优化企业资产结构，提高企业资产的总体质量，最终建立起符合市场经济要求的、更富有竞争力的资产组织体系。 上市公司资产重组是一个内涵和外延都较宽泛的概念。从内涵上看，它是指以上市公司为主体而从事的各种资产重组。从外延上看，上市公司资产重组既包括公司上市前的资产重组（股份制改组式的资产重组），又包括企业上市后的资产重组；既包括上市公司之间的兼并和收购，又包括上市公司兼并收购非上市公司以及非上市公司并购上市公司；既包括国有企业海外上市，又包括外资并购中国的国有企业。一般来说，上市司资产重组的模式可以分为初次重组模式和再次重组模式。 初次重组是企业为了向募集股份并上市交易，通过合并、分离等资产重组方式，调整股东权益和财务组织结构，以达到有关法规和证券监管机构的要求的过程。上市的企业在上市前，对企业结构的重组常常采用以下一种或多种资产重组模式进行：（1）整体改组上市模式；
精神分裂症的病因是什么 精神分裂症是一种精神方面的疾病，青壮年发生的概率高，一般 在16～40岁间，没有正常器官的疾病出现，为一种功能性精神病。 精神分裂症大部分的患者是由于在日常的生活和工作当中受到的压力 过大，而患者没有一个良好的疏导的方式所导致。患者在出现该情况 不仅影响本人的正常社会生活，且对家庭和社会也造成很严重的影响。 精神分裂症常见的致病因素： 1、环境因素：工作环境比如经济水平低低收入人群、无职业的人群中，精神分裂症的患病率明显高于经济水平高的职业人群的患病率。还有实际的生活环境生活中的不如意不开心也会诱发该病。 2、心理因素：生活工作中的不开心不满意，导致情绪上的失控，心里长期受到压抑没有办法和没有正确的途径去发泄，如恋爱失败， 婚姻破裂，学习、工作中不愉快都会成为本病的原因。 3、遗传因素：家族中长辈或者亲属中曾经有过这样的病人，后代会出现精神分裂症的机会比正常人要高。 4、精神影响：人的心里与社会要各个方面都有着不可缺少的联系，对社会环境不适应，自己无法融入到社会中去，自己与社会环境不相
适应，精神和心情就会受到一定的影响，大脑控制着人的精神世界， 有可能促发精神分裂症。 5、身体方面：细菌感染、出现中毒情况、大脑外伤、肿瘤、身体的代谢及营养不良等均可能导致使精神分裂症，身体受到外界环境的 影响受到一定程度的伤害，心里受到打击，无法承受伤害造成的痛苦，可能会出现精神的问题。 对于精神分裂症一定要配合治疗，接受全面正确的治疗，最好的 疗法就是中医疗法加心理疗法。早发现并及时治疗并且科学合理的治疗，不要相信迷信，要去正规的医院接受合理的治疗，接受正确的治 疗按照医生的要求对症下药，配合医生和家人，给病人创造一个良好 的治疗环境，对于该病的康复和痊愈会起到意想不到的效果。
卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规 范(试行)》的通知 【法规类别】采供血机构和血液管理 【发文字号】卫办医政发[2009]189号 【失效依据】国家卫生计生委办公厅关于印发造血干细胞移植技术管理规范(2017年版)等15个“限制临床应用”医疗技术管理规范和质量控制指标的通知 【发布部门】卫生部(已撤销) 【发布日期】2009.11.13 【实施日期】2009.11.13 【时效性】失效 【效力级别】部门规范性文件 卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规范（试行）》的通知 （卫办医政发〔2009〕189号） 各省、自治区、直辖市卫生厅局，新疆生产建设兵团卫生局： 为贯彻落实《医疗技术临床应用管理办法》，做好脐带血造血干细胞治疗技术审核和临床应用管理，保障医疗质量和医疗安全，我部组织制定了《脐带血造血干细胞治疗技术管理规范（试行）》。现印发给你们，请遵照执行。 二〇〇九年十一月十三日
脐带血造血干细胞 治疗技术管理规范（试行） 为规范脐带血造血干细胞治疗技术的临床应用，保证医疗质量和医疗安全，制定本规范。本规范为技术审核机构对医疗机构申请临床应用脐带血造血干细胞治疗技术进行技术审核的依据，是医疗机构及其医师开展脐带血造血干细胞治疗技术的最低要求。 本治疗技术管理规范适用于脐带血造血干细胞移植技术。 一、医疗机构基本要求 （一）开展脐带血造血干细胞治疗技术的医疗机构应当与其功能、任务相适应，有合法脐带血造血干细胞来源。 （二）三级综合医院、血液病医院或儿童医院，具有卫生行政部门核准登记的血液内科或儿科专业诊疗科目。 1.三级综合医院血液内科开展成人脐带血造血干细胞治疗技术的，还应当具备以下条件： （1）近3年内独立开展脐带血造血干细胞和（或）同种异基因造血干细胞移植15例以上。 （2）有4张床位以上的百级层流病房，配备病人呼叫系统、心电监护仪、电动吸引器、供氧设施。 （3）开展儿童脐带血造血干细胞治疗技术的，还应至少有1名具有副主任医师以上专业技术职务任职资格的儿科医师。 2.三级综合医院儿科开展儿童脐带血造血干细胞治疗技术的，还应当具备以下条件：
上市公司资产重组财务会计问题分析 当前经济形势下，上市公司资产重组问题引起了社会的高度关注。上市公司资产重组有着一定的必然性，上市公司资产重组，有利于产业结构的条恒，降低公司发展风险，但是上市公司资产重组会给我国证券行业的发展带来了一定的影响。在上市公司资产重组活动中，财会信息是该活动顺利开展的关键，一旦财会信息出现问题，就会束缚上市公司资产重组，不利于我国证券行业的稳定发展。因此，在上市公司资产重组过程中，做好财务会计工作至关重要。 一、上市公司资产重组的概述 所谓上市公司资产重组就是对上市公司对内进行优化的一种经济活动，包括公司规模、公司经营成本等。对于上市公司而言，其资产结构直接影响到自身的发展，对资产结构进行优化，可以大大提高资产利用效率，促进公司产业结构的调整，推动公司的更好发展。近年来，研究学者对上市公司资产重组的研究越来越深入，有研究学者认为，上市公司资产重组会影响到公司出资人的财产权和公司法人的财产权，通过资产重组达到公司资产最优配置，能够增强公司的市场竞争力，有利于公司的稳定发展。也有学者认为资产重组就是将一种财产转变为另一种财产，对资源进行合理的整合，这一观点强调的是交易的重要性。 二、上市公司资产重组财务会计问题 (一)资产公允值问题
所谓资产公允值是指以公平、公正、公开的方式确定的交易价格。对于资产重组这种活动而言，资产公允值一定程度上决定了资产重组活动能够顺利开展，合理的资产公允值有利于资产重组活动的开展；反之，不合理的公允值则会影响到资产重组活动。目前来看，我国市场经济体制还不够完善，相关法律法规制度不够健全，对资产重组活动越发有效的保障和约束，从而造成资产公允值的公信力下降。同时，在上市公司资产重组活动中，上市公司对资产缺乏有效的评估，对上市公司的资产缺乏全面的掌控，影响到了资产公允值的确定。 (二)会计信息披露不全面 在上市公司资产重组活动中，会计信息披露不全面是一个比较凸显的问题。当前，上市公司资产重组后，财务指标标准还没有明确、统一，在这种情况下，上市公司资产重组后的财务报表和置换、分离以及诸如的资产评估表等工作难以顺利的开展，很容易出现信息不明、会计信息失真的现象。另外，上市公司资产重组活动中，会计信息的准确度得不到有效的保障，对上市公司资产重组后的财务活动缺乏有效的监管，不能全面地掌控财务信息，虚假信息充斥在公司财务之中，从而危及到上市公司的发展。 (三)会计利润的控制问题 上市公司资产重组的目的就是优化资源配置，获得更好的效益。就目前来看，我国现代公司制度起步较晚，与之相关匹配的法律法规制度还不够完善，使得许多上市公司在资产重组的时候喜欢钻法律空子，在财务会计工作中做手脚，出现一些弄虚作假的行为，造成会计
精神分裂症应该怎么治疗 1、坚持服药治疗 服药治疗是最有效的预防复发措施临床大量统计资料表明，大多数精神分裂症的复发与自行停药有关。坚持维持量服药的病人复发率为40%。而没坚持维持量服药者复发率高达80%。因此，病人和家属要高度重视维持治疗。 2、及时发现复发的先兆，及时处理 精神分裂症的复发是有先兆的，只要及时发现，及时调整药物和剂量，一般都能防止复发，常见的复发先兆为：病人无原因出现睡眠不好、懒散、不愿起床、发呆发愣、情绪不稳、无故发脾气、烦躁易怒、胡思乱想、说话离谱，或病中的想法又露头等。这时就应该及时就医，调整治疗病情波动时的及时处理可免于疾病的复发。 3、坚持定期门诊复查 一定要坚持定期到门诊复查，使医生连续地、动态地了解病情，使病人经常处于精神科医生的医疗监护之下，及时根据病情变化调整药量。通过复查也可使端正人及时得到咨询和心理治疗解除病人在生活、工作和药物治疗中的各种困惑，这对预防精神分裂症的复发也起着重要作用。 4、减少诱发因素 家属及周围人要充分认识到精神分裂症病人病后精神状态的薄弱性，帮助安排好日常的生活、工作、学习。经常与病人谈心，帮助病人正确对待疾病，正确对待现实生活，帮助病人提高心理承受能力，学会对待应激事件的方法，鼓励病人增强信心，指导病人充实生活，使病人在没有心理压力和精神困扰的环境中生活。 首先是性格上的改变，塬本活泼开朗爱玩的人，突然变得沉默寡言，独自发呆，不与人交往，爱干净的人也变的不注意卫生、生活
懒散、纪律松弛、做事注意力不集中，总是和患病之前的性格完全 相悖。 再者就是语言表达异常，在谈话中说一些无关的谈话内容，使人无法理解。连最简单的话语都无法准确称述，与之谈话完全感觉不 到重心。 第三个就是行为的异常，行为怪异让人无法理解，喜欢独处、不适意的追逐异性，不知廉耻，自语自笑、生活懒散、时常发呆、蒙 头大睡、四处乱跑，夜不归宿等。 还有情感上的变化，失去了以往的热情，开始变的冷淡、对亲人不关心、和友人疏远，对周围事情不感兴趣，一点消失都可大动干戈。 最后就是敏感多疑，对任何事情比较敏感，精神分裂症患者，总认为有人针对自己。甚至有时认为有人要害自己，从而不吃不喝。 但是也有的会出现难以入眠、容易被惊醒或睡眠不深，整晚做恶梦或者长睡不醒的现象。这些都有可能是患上了精神分裂症。 1.加强心理护理 心理护理是家庭护理中的重要方面，由于社会上普遍存在对精神病人的歧视和偏见，给病人造成很大的精神压力，常表现为自卑、 抑郁、绝望等，有的病人会因无法承受压力而自杀。家属应多给予 些爱心和理解，满足其心理需求，尽力消除病人的悲观情绪。病人 生活在家庭中，与亲人朝夕相处，接触密切，家属便于对病人的情感、行为进行细致的观察，病人的思想活动也易于向家属暴露。家 属应掌握适当的心理护理方法，随时对病人进行启发与帮助，启发 病人对病态的认识，帮助他们树立自信，以积极的心态好地回归社会。 2.重视服药的依从性 精神分裂症病人家庭护理的关键就在于要让病人按时按量吃药维持治疗。如果不按时服药，精神病尤其是精神分裂症的复发率很高。精神病人在医院经过一系统的治疗痊愈后，一般需要维持2~3年的
卫生部关于印发《脐带血造血干细胞库设置管理规范(试行)》的通知 发文机关：卫生部(已撤销) 发布日期： 2001.01.09 生效日期： 2001.02.01 时效性：现行有效 文号：卫医发(2001)10号 各省、自治区、直辖市卫生厅局： 为贯彻实施《脐带血造血干细胞库管理办法（试行）》，保证脐带血临床使用的安全、有效，我部制定了《脐带血造血干细胞库设计管理规范（试行）》。现印发给你们，请遵照执行。 附件：《脐带血造血干细胞库设置管理规范（试行）》 二○○一年一月九日 附件： 脐带血造血干细胞库设置管理规范（试行） 脐带血造血干细胞库的设置管理必须符合本规范的规定。 一、机构设置 （一）脐带血造血干细胞库（以下简称脐带血库）实行主任负责制。 （二）部门设置 脐带血库设置业务科室至少应涵盖以下功能：脐带血采运、处理、细胞培养、组织配型、微生物、深低温冻存及融化、脐带血档案资料及独立的质量管理部分。 二、人员要求
（一）脐带血库主任应具有医学高级职称。脐带血库可设副主任，应具有临床医学或生物学中、高级职称。 （二）各部门负责人员要求 1．负责脐带血采运的人员应具有医学中专以上学历，2年以上医护工作经验，经专业培训并考核合格者。 2．负责细胞培养、组织配型、微生物、深低温冻存及融化、质量保证的人员应具有医学或相关学科本科以上学历，4年以上专业工作经历，并具有丰富的相关专业技术经验和较高的业务指导水平。 3．负责档案资料的人员应具相关专业中专以上学历，具有计算机基础知识和一定的医学知识，熟悉脐带血库的生产全过程。 4．负责其它业务工作的人员应具有相关专业大学以上学历，熟悉相关业务，具有2年以上相关专业工作经验。 （三）各部门工作人员任职条件 1．脐带血采集人员为经过严格专业培训的护士或助产士职称以上卫生专业技术人员并经考核合格者。 2．脐带血处理技术人员为医学、生物学专业大专以上学历，经培训并考核合格者。 3．脐带血冻存技术人员为大专以上学历、经培训并考核合格者。 4．脐带血库实验室技术人员为相关专业大专以上学历，经培训并考核合格者。 三、建筑和设施 （一）脐带血库建筑选址应保证周围无污染源。 （二）脐带血库建筑设施应符合国家有关规定，总体结构与装修要符合抗震、消防、安全、合理、坚固的要求。 （三）脐带血库要布局合理，建筑面积应达到至少能够储存一万份脐带血的空间；并具有脐带血处理洁净室、深低温冻存室、组织配型室、细菌检测室、病毒检测室、造血干/祖细胞检测室、流式细胞仪室、档案资料室、收/发血室、消毒室等专业房。 （四）业务工作区域应与行政区域分开。
2012年第1期下旬刊（总第469期） 时 代 金 融 Times Finance NO.1，2012 （CumulativetyNO.469） 资产重组的实质就是产权的流动和转让，也就是指两个以上的法定主体之间所发生的财产所有权及其派生的占有权、使用权、收益权和处分权等各项权能的部分或全部有偿转移的法律行为。资产重组的运作必然要涉及财务、会计、法律、税收、土地等有关实务内容，这些既是资产重组运作的重点，又是资产重组运作的难点。 一、企业资产重组 我国自20世纪80年代初引进企业资产重组概念以来，特别是近些年来，随着我国社会主义经济体制的初步建立、科学技术的迅速发展、买方市场的逐步形成、经济全球化的不断加快以及我国加WTO以后，政府、企业和学术界都意识到发展企业资产重组的重要性，开始注重企业资产重组的发展。目前，我国的企业资产重组发展已初具规模，良性发展的局面真正逐渐形成。同时，资产重组在很大程度上是以货币或有价证券为手段，是有限的经济资源在市场各主体之间进行再分配的过程。它体现为价值的运动和利益的转移。因此，资产重组是企业进行资本经营的重要环节。当企业通过增量的方式，例如企业并购来整合企业时，它既打破了原有的资本结构又打破了原有的资产结构，使资产进行重新组合。当企业通过存量调整来改善企业的资产结构时，也离不开企业的重新组合。所以，无论是增量调整，还是存量调整，企业总离不开通过资产重组来进行资本经营。 二、企业资产重组的财务问题及解决措施 （一）关于并购中的债务重组与不良资产的处理 现代企业资产重组科学技术已经可以提供多种流程贯通一气的方法和技术。我国的企业资产重组中的财务问题在很大程度上仍遵循“大而全”、“小而全”的管理模式，往往自成一个封闭的系统，与开放式的全球制造和供应链管理模式相去甚远。企业的生产设计往往只考虑生产过程本身，而没有考虑供应链对企业竞争力的影响：各企业的生产经营活动基本上是各自为政，相互脱节，供应商、制造商、分销商之间缺乏战略合作关系，没有形成一条完整的供应链；企业内企业资产重组机构及资源配置重叠，企业资产重组活动分散且效率低下，库存量大、资金积压和资产重组成本居高不下现象比较严重；大型企业较多地追求所需物品的高自制率而忽视企业自己的核心竞争力，影响和制约了产品的质量及其市场竞争力。在这种情况下，系统深入地分析药品制造企业企业资产重组的中的财务问题现状及存在的主要问题，通过实施资产重组管理创新，以提高企业的管理水平，降低资产重组成本，提升其在国内、国际市场的竞争力，对实现我国企业的可持续发展，具有重要的战略和理论意义。 （二）公司合并的两种会计处理方法 目前本人在农干校财务科工作，虽然资产重组一再成为热点，但并非只要重组就可以真的改善学校的经营和发展，例如，国家股无偿划拨类型的股权转移学校发展变化具有滞后性。通常重组当年学校发展并无改善，明显的学校的发展改善多发生在重组的第二年，但是在此之后，学校发展增长率又转为下降，说明增长的持续性不强；政府介入较深的重组主要从两个方面带来学校发展的改善。相比之下，由于重组领域选择不当或自身的历史包袱过重等原因，资产重组对学校发展的影响尚不明朗。面对如此巨大的资产重组供应网络，公司如果没有建立有效而完整的资产重组系统是很难满足企业飞速发展要求的。所以，公司如何建立适合自身企业发展的资产重组系统，实现企业柔性生产和及时供货，使企业从资产重组方面来进一步降低成本具有非常重要的意义。 近几年来，国内外关于资产重组的理论与实践有很多专家进行了研究，但针对企业在供应链环境下资产重组中的财务问题的研究尚不多见。但在当前全球制造的大环境下，包括企业在内的我国制造企业融入全球供应链的程度及供应链管理水平还比较低，与国际先进水平相比有较大的差距。 由于我国加入WTO的时间较短，企业还没有完全适应市场经济的激烈竞争，加之我国企业的市场体系不健全和市场发育还不是很完善，从而造成我国企业市场流通秩序比较混乱。因此，在我国企业流通领域里出现众多的资产重组企业，而这些企业由于其规模和市场占有率都比较小，使得我国企业流通领域内形成市场分散且效益低下的不利局面。这样很难参与国际领域的市场竞争，而企业供应链所表现出的这些特点都与我国政府调控不力有着密切相关。正是由于我国政府的调控不力而造成国内企业的数量众多和经营分散的不利局面出现，企业要想生存和发展就必然会导致企业间无序竞争和过度竞争，使得企业的经济效益非常低和缺乏市场竞争力。 总之，资产重组作为一种全新的管理思想，势必会对我国的企业和大型生产企业产生深远的影响，它的出现将改变企业传统的粗放式的资产重组管理观念，使企业尽快适应加入WTO后的市场竞争影响，积极对自己企业的资产重组管理进行精益化改进，努力提高企业的资产重组管理水平，从而保持企业的核心竞争力。资产重组思想与战略思想一样，它主要是企业在生产过程中杜绝生产管理中的一切无价值的活动，从而实现企业生产系统的价值最大化，这样一来也才能为企业实现企业价值最大化的目标提供了有力保证。所以，企业采用资产重组思想来实现企业生产管理系统价值最大化的原理与企业采用战略思想实现企业价值最大化的原理是相同的。 三、结论 总之，企业间的兼并收购在会计上表现为股权投资。在我国，随着社会主义市场经济的发展和市场经济体制的确立，企业相互持股、合并的情况已经屡见不鲜。随着现代企业制度的逐步建立，证券市场的日益发展、完善，企业兼并、控股的现象将会越来越多，而其中解决财务问题将越来越重要。 参考文献 [1]石朝宏.并购中目标企业价值评估方法研究[D].重庆大学硕士学位论文，2008. [2]王城栋.并购中目标企业价值评估研究[D].华中科技大学硕士学位论文，2008. [3]翟雪改.企业并购的财务风险探析[J].华东经济管理，2009年7月：133. 作者简介：赵建秀 (1978-)，女，汉族，淮安市淮阴区农干校财务科，研究方向：企业管理、行政事业单位财务管理。 （责任编辑：刘晶晶） 企业资产重组中的财务问题探讨 赵建秀 （淮安市淮阴区农干校，江苏 淮安 223001） 【摘要】在企业兼并这种主要的资产重组形式中，财务问题涉及面较广，它包括目标公司的评估，公司兼并的资金来源与兼并费用，兼并价格与成本的确定，一般财务处理以及商誉问题等。本文主要探讨企业资产重组中存在的财务问题，并提出解决措施。 【关键词】企业 资产重组 财务风险 10 Times Finance