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¢0321£ National Animosity and Cross-Border Alliances

¢0321£ National Animosity and Cross-Border Alliances
¢0321£ National Animosity and Cross-Border Alliances

NATIONAL ANIMOSITY AND CROSS-BORDER ALLIANCES

ILGAZ ARIKAN ODED SHENKAR

The Ohio State University

We extend the cross-border strategic alliance knowledge base by introducing dyad-specific antagonism (animosity between nation pairs)and hold that the formation and the type of firm-level cross-border alliances are nontrivially impacted by conflicting relations and animosity between their home nations.We examine the formation of alliances between firms among nation-dyads with and without a history of conflicts.The frequency and magnitude of conflicts increase the perception of likelihood of opportunism,and dyad-specific risks materially affect the context in which firms make alliance decisions.As animosity between two nations increases,the number and the probability of forming alliances within the dyad the nations form decreases.Conditional on the expected number of alliances,increased antagonistic actions of nations outside the dyad and dissimilarity in the historical conflicts that each nation has engaged in outside the dyad (i)increase the number of equity alliances and (ii)decrease the number of nonequity alliances as a proportion of total alliances.We find positive main effects of learning to contract through prior experience only for equity (vs.nonequity)alliances.The reputation effects of antagonism based on relationships with nations outside of the dyad negatively moderate the positive learning effects of prior equity alliance experience.

Cross-border strategic alliance research in man-agement and international business borrows exten-sively from economics and sociology;however,po-litical science and international relations have not been a substantial source until recently (Delios &Henisz,2003;King &Zheng,2001).This is surpris-ing,given the rich interface between political sci-ence and international business in such areas as institutional analysis,governance choices under political risk,government role,and evolving dy-namics in geopolitical settings.We propose that strategic alliances research can further benefit from political science and international relations litera-tures on conflicts between nation-states in which interfirm alliances are embedded and look beyond nation-specific risk factors by focusing on factors that are nation-dyad-specific and that affect firms.

In this article,we connect these two literatures to shed light on the alliance partner selection process.We hold that the formation and type of alliances are nontrivially impacted by conflict relations between their home nations when firms perceive a greater likelihood of opportunism.We extend the current work on political hazards that looks at nation-spe-cific risk factors and introduce a new approach by studying dyadic factors (i.e.,the nation of the firm seeking to enter an alliance).

Numerous explanations have been advanced to elucidate the motives for alliance formation,in-cluding learning,asset leveraging,partner knowl-edge search (Cohen &Levinthal,1990;Kale,Singh,&Perlmutter,2000;Lane,Salk,&Lyles,2001),knowledge creation (Reuer,Zollo,&Singh,2002),new market entry,transaction costs economizing (Hennart,1988;Mowery,Oxley,&Silverman,1996),interest alignment (Harrigan,1985),and tap-ping overlapping market segments (Peteraf &Shan-ley,1997).Worries about alliance underperfor-mance,such as misalignment of partner interests and lack of skills for managing partnership in un-familiar foreign environments (Shenkar &Zeira,1987),have also been proposed as influences on formation decisions.(Hamel,1991;Hill &Hellrie-gel,1994).Further,partner selection has been stud-

We are indebted to associate editor Kyle Mayer and three anonymous reviewers for their help in improving this study.We are also grateful to Asli Arikan,Lorraine Eden,Witold Henisz,Joe Mahoney,Edward Mansfield,Anita McGahan,Jackson Nickerson,Joanne Oxley,Jor-dan Siegel,and Bernard Yeung for discussions and feed-back on earlier versions.We gratefully acknowledge the generous research support from the Mershon Center for International Security Studies at the Ohio State Univer-sity,and the OSU CIBER.The usual caveats apply.

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?Academy of Management Journal 2013,Vol.56,No.6,1516–1544.

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ied as a transactional feature(Reuer et al.,2002), wherein previous cooperative experiences favor friends over strangers and strangers over acquain-tances(Li,Eden,Hitt,&Ireland,2008).Trust was identified as the operative construct that distin-guished potential partners,given exchange vulner-abilities and firms’governance mechanisms(Bar-ney&Hansen,1994).

In this study,we advance the argument that na-tional animosity,for which we use past national conflict as proxy,can materially bias alliance for-mation.In particular,we argue that firms’decision to form alliances and the level of commitment em-bedded in organizational boundary choices will be strongly influenced by the existence of antagonism between nation-dyads because firms perceive a greater likelihood of opportunism in these con-texts.During alliance formation,a complex and multilevel process occurs.A variety of economic and quasi-rational noneconomic assessments of costs and benefits,filtered through behavioral pro-cesses of perception and interpretation(Tallman& Shenkar,1994),guide this process.Therefore,de-cisions for or against forming alliances with partic-ular partners are influenced by both macrolevel determinants,such as societal,political,institu-tional,and national context(Henisz,2000a),and microlevel determinants,such as individual deci-sion-making heuristics,stereotypes,and prejudices (Cyert&March,1963).These effects extend to par-ticular country selection,entry mode,and level of commitment in new alliances.Thus,we focus on how political,cultural,and historical factors shape cross-border alliance formation.

Noting endogeneity concerns(Shaver,1998),we offer that the context of conflict between partners’nations biases executives toward a preselected set of partners hailing from“friendly”nations rather than from the full pool that an optimizing approach would indicate.Therefore,we start with the entire population of countries available at the time of transaction and focus on initial decisions to form alliances with firms in each nation-pair(nation-dyad).We assert that,other things being equal,the existence(or lack thereof)of animosity within a dyad impacts partner choice.We empirically tested our arguments using comprehensive panel data that combine various data sources that cover over-lapping time periods:nation-dyad trade levels,na-tion-dyad conflict,and firm-level alliances aggre-gated at the nation-dyad level.

This article is organized as follows.First,we explain the nature of the dyadic political hazards,define nation-level conflict,and examine the ef-fects of animosity in the form of political and eco-nomic conflicts on alliance formation decisions. We then hypothesize the formation of cross-border alliances between firms that belong to nation-dy-ads,given the differences in historical and current conflicts.These nation-dyads constitute a network of conflicting,as well as of nonconflicting,nations. We distinguish between equity and nonequity alli-ances because level of commitment made by firms entering each type differs significantly(Henisz, 2000a),and equity alliances are more clearly de-fined structures with direct implications for learn-ing(Anand&Khanna,2000).Furthermore,build-ing on Mayer and Argyres(2004),we posit that firms’experiences in learning to contract may mit-igate the effects of animosity;both direct and indi-rect experience may moderate relationships in alli-ance formation.We present our results and discuss the implications of the findings.

THEORY DEVELOPMENT

History matters in international business.History not only helps uncover the pattern by which firms behave,but also contributes to explanation of tem-poral effects—in particular,firm choices(Jones& Khanna,2006).A very significant component of history,and directly relevant for cross-border firm behavior,is conflict.Past or current conflicts be-tween nations affect firm choices because firms are nested in nation-states(Shenkar&Arikan,2009). Firms ally with other firms among these nests,after they select a partner for partner-specific(Kogut& Singh,1988)and context-specific attributes(Lane et al.,2001).Here,we focus on conflict among nations,defined as divergence of interests and op-posing actions(Deutsch,1973).An extensive body of research explores the causal relationship be-tween political and economic conflicts and their consequences for international trade and relations. Political and economic conflicts are interrelated and,over time,as conflicts turn from simple com-petition to threat,display,and use of force,they often deteriorate into military confrontation.When conflicts are frequent or when they escalate,“con-siderable animosity,hatred and prejudice are im-printed”in the memories of the parties(Bar-Tal, 2000:355).Animosity,defined by the Oxford En-glish Dictionary as“hostility of mind tending to break out into action,active hatred or enmity,”then becomes part of the parties’societal beliefs and cultures,passed from generation to generation,be-

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coming a self-fulfilling reality(Bar-Tal,2000).An-imosity increases as the severity and violence of a conflict increase,affecting more people.

In political science and international relations research,attention has been paid to the justification of conflict and the actions taken to legitimize its outcome.Perceptions of fairness of conduct during a conflict,especially in aggravated cases such as wars,shape the setting in which cross-border busi-ness is subsequently conducted.Conflicts disrupt economic activity for a long time(Anderton& Carter,2001),but the duration and severity of im-pact vary by conflict motivation.A conflict about gaining tangibles(e.g.,access to land and re-sources)versus intangibles(e.g.,honor,prestige) (Hirshleifer,1998),can be resolved without re-course to war since the cost of aggression is deemed to outweigh potential gain.Gaining intangibles will have longer-term impact,not only because it is a zero-sum game but also because conflicting parties soon discover alternatives to war when they realize the potential losses(Hirshleifer,1998).

In international economics,animosity and con-flict have been discussed primarily in relation to trade,in work showing that prolonged economic conflict leads to economic animosity between na-tions(Barbieri&Levy,1999).Nations with limited resources are dependent on their partners and im-port goods and services from nations that have resources in abundance.Economic animosity re-sults from increased imbalance of trade and creates perceptions of economic dominance or aggression of the exporting countries(Nijssen&Douglas, 2004).Some suggest that geographic proximity in-creases conflict and war propensity(Pollins,1989); others offer the view that by enhancing the fre-quency of exchange and cultural interaction,prox-imity reduces conflict and boosts trade(Polachek, 1980).Historically,international trade has pre-ceded governance mechanisms between firms.In the17th century,trade was led by state-owned firms(e.g.,England’s East India Company),which enabled nations to exert monopoly power over trade routes and colonies;firms represented their nations and were directly affected by interna-tional relations,which were interrupted by con-flicts and resumed at the end of hostilities(Lake &O’Mahony,2004).

In research in business and management,appli-cations of the concept of animosity have been largely confined to consumer behavior(Klein, 2002)and negotiations(Gruder,1971).For exam-ple,“country-of-origin effect”and“consumer eth-nocentrism”are used to explain why consumers are less inclined to buy foreign goods and services originating in countries they feel animosity toward (Klein&Ettenson,1999).In negotiations and social identity research,animosity has been shown to im-pact in-versus out-group identification as well as negotiation dynamics and outcomes(Tse,Francis, &Walls,1994),social perceptions(Brewer,1979), conflict resolution models,and cognitive biases (Pruitt&Rubin,1986).

Only very recently has firm-level international research begun to cast partner selection not as an exogenous process,but as a dimension of the deci-sions and choices firms make(e.g.,Li et al.,2008). Despite its salient effects in creating socioeco-nomic,political,and contractual hazards(Henisz, 2000a),the impact of animosity on the formation of alliances has been largely neglected.The field has developed theoretical precursors(e.g.,Henisz, 2000a,2000b;Kogut&Singh,1988),but those have not been extended to the nation-firm interactional level,though institutional,cultural,and contract-ing hazards around governance choices have been studied in general terms(Delios&Beamish,1999; Roberts&Greenwood,1997).

Effects of Conflict on Alliance Formation Managers make decisions in the context of inter-national relations and sentiments,and it is reason-able to assume that some of the considerations they make as individuals or consumers also influence their corporate decisions(Hutzschenreuter,Peder-sen,&Volberda,2007).Firms that do business where contracting parties feel animosity toward one another will lose trust and observe increased exchange hazards.A wide spectrum of hazards can increase the transaction costs of collaborative ex-change(Williamson,1983),including appropria-tion(Oxley,1997),environmental uncertainty (Luo,2007),and coordination difficulties(Hennart, 1988).A broad range of research on governance choices has,in explaining how firms organize transaction risks and costs,focused on how re-peated transactions increase trust and familiarity in alliances(Gulati,1995)and in acquisitions(Walker &Weber,1984).In volatile environments,such as contexts in which national antagonism exists,in-creased perceptions of opportunistic behavior and appropriability hazards may require firms to seek mutual hostages and credible commitments to off-set potential hazards in newly formed agreements (Williamson,1983).

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Governance forms,ranging from unilateral(e.g., supply contracts)to bilateral contractual agree-ments such as alliances and joint ventures(Oxley, 1997)would follow from least to most hierarchical categories.While wholly owned subsidiaries or ac-quisitions represent more credible commitments, firms would shy away from them in favor of alli-ances and equity alliances as a way to mitigate the risk of full ownership and control(Reuer,2001). Compared to looser alliances,equity alliances rep-resent higher partner commitment(Inkpen&Cur-rall,2004)and lower relational risks,as a result of mutual forbearance(Tallman&Shenkar,1994).In addition,exchange hazards are closely intertwined with political hazards(Anderson&Gatignon, 1986).These hazards are implicitly present in ev-ery exchange in a foreign country and pose a threat to firms through taxation of earnings,instability and unpredictability of regulatory environments, expropriation of economic rents,and lack of pro-tection of property rights(Madhok,1997). Magnified by political hazards,firms entering nations with known and existing antagonism may face increased transaction costs and exchange hazards(Le Billon,2001)and perceive greater likelihood of opportunism due to heightened ad-versarial relations(Kastner,2007).For example, firms entering hostile markets(unlike their domestic counterparts entering friendly nations)may face in-creased risks,such as trade barriers and embargoes (Morrow,1999),discouraging security externalities (Gowa,1994),and postentry trade sanctions (Gartzke,Li,&Boehmer,2001).When firms operate in a hostile environment,retention of flexibility may gain salience,and commitments in specific assets may decrease(Henisz,2000b).Firms orga-nize to avoid ownership and seek to retain flexibil-ity(Williamson,1979).If a firm is already in such an environment,flexibility may be lost,and it be-comes desirable to control transactions(Anderson &Gatignon,1986).Hence,external tensions exas-perate the friction that asset specificity brings and impacts a firm’s decision to organize an exchange. Thus the pressure to maintain credibility in an institutional environment among political jurisdic-tions of varying statures,availability,and enforce-ment credibility gain salience(Williamson,2010). If firms mistrust a potential partner from an adversarial nation and think their counterpart will be more opportunistic(Williamson,1993), governance choices will reflect precautionary moves for the ex post possibility of hazards and the likelihood of opportunism.Firms would then base organization of their governance on mutual hos-tages,highlighting credible commitments ex ante (Henisz&Williamson,1999),and write contracts to deter opportunism and safeguard exchange.How-ever,to view contracts as the only safeguard against opportunism underestimates the“psychological impacts of contracts on the exchange and ongoing relationships”(Weber&Mayer,2011:69),because proper framing of contracts to engender trust be-tween potential partners in nations with known animosity or conflicts is critical in the formation of alliances.

Prior research has focused on how multinational corporations(MNCs)operate in foreign markets in which political hazards increase transaction costs (e.g.,Luo,2007).We propose that the historical relation between two nations creates additional transactional hazards for firms from these nations. Instead of focusing only on the political hazards due to foreignness,we introduce a new construct—nation-dyad conflict—that directly impacts histor-ical context and transactions between two nations. Hence,when firms from Japan and China form an alliance and decide to enter Russia,these firms both will evaluate the potential exchange hazards in Russia,and on the basis of the history of con-flicts,will require different levels of safeguards against varied perceptions of opportunism.Further-more,the existence of hostilities(or lack thereof) between two nations impacts the administrative and political distance between them.When two nations have hostility between them,the distance between them is higher,and the ties are weaker, which inhibits trade(Ghemawat,2001),and the perceived likelihood of opportunism would in-crease for firms from both nations.National con-flicts would require credible commitments pro-tecting potential partners against opportunistic behavior(Williamson,1983).Despite credible commitments and reciprocal exposure between two partners,should conflicts increase into na-tional hostilities,or escalate into military action, high possible exchange hazards and perceived likelihood of opportunism(e.g.,expropriation risks,breach of property and control rights,con-tract enforcement issues)strongly deter firms from forming alliances.Hence:

Hypothesis1.As the animosity between two nations increases,the number of cross-border firm-level alliances within the dyad they form decreases.

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Mechanisms That Influence Conflict and Individuals

The underlying mechanisms that influence how conflict impacts individuals can be examined on two levels:the societal,which affects the nations of which individuals are members,and the individ-ual,which contributes to how an individual views and interprets exogenous factors.Individuals are inherently affected by social sentiments,which are affected by cultural aspects,history,and how his-tory is retained in the minds of people as collective memory(Klein,2002).The sentiments that affect individuals’level of trust and decision making hence affect economic exchange.As individuals who share common attributes and experiences ac-quire and accumulate memories,remembrance of these collective assets gains validity in a group context(Mannheim,1997).

At the societal level,the collective memories in-fluence and shape national policies.At the individ-ual level,the collective memory manifests itself as stereotyping and directly applies to formation of in-and out-group perceptions(Linville,Salovey,& Fischer,1986).Individuals base generalizations about a category on attributes pertaining to a group identity,and categorizations aggregate into group identities.Individuals use these cognitive catego-rizations,or stereotypes,to process information about others they interact with(Hamilton&Trolier, 1986).On the basis of how similar the traits of a perceiver and a focal group are,categories of in-group and out-group are formed.Individuals per-ceive,retain,and process information with more favorable attributes about in-group than out-group members(Hamilton&Trolier,1986).

In the context of firms,if managers have negative collective memory about a potential partner,and if they differentiate between their own and the poten-tial partner’s attributes in view of historical con-flicts and cultural facets,they would label the part-ner as out-group.The homogeneous categorizations most often would be biased and prejudiced,result-ing in strict contracting parameters or outright dis-missal of potential alliances.Thus,when two par-ties have the potential to interact,one party’s prior beliefs about the other party will have a strong impact on a decision to ally.For instance,if infor-mation gathering and processing occur under the shadow of suspicion of future friction due to con-trasting values and beliefs(Bar-Tal,1997),stereo-types,and national prejudices(Desivilya,1998), either contracts will reflect such precautionary mo-tivations,or partners will seek transaction cost–reducing substitutes such as trust(Gulati,1995;Li et al.,2008).

Network Effects on Conflicts and Alliances Nations constitute a network through institu-tional,financial,ideological,and security ties among them that are such that the global network is composed of many“smaller worlds.”The dynamic nature of the global network is provisional on the complex interactions within and between these smaller worlds.Ideological and economic conflicts, as well as concords between nations,influence the patterns by which firms operate and organize their ownership structures(Kogut&Walker,2001).Just like firms,nations in a global network expect pre-dictability,reliability,and competence from each other(Kilgour&Zagare,1991).As nations have information about others’past actions,the predict-ability of future conduct increases.Foresight based on credibility improves concerns about vulnerabil-ity to future opportunistic behavior.Nations deter each other by promising a punishment that is deemed a credible threat,under the assumption that nations do not often change their ideologies but do vary in their economic dominance over time,creating an imbalance in each dyad in the network comprising the nations(Powell,1989). Imbalanced dyadic relations1arise from complex interactions between nations and may result in in-tended or unintended conflict(Maoz,1990).Imbal-ance in a dyad occurs when(i)a nation experiences economic dominance or aggression on the part of another country,for instance in the form of trade imbalance(Nijssen&Douglas,2004),or(ii)is im-pacted by the opportunistic and exploitative nature of military or economic alliances by other nations (Maoz,Terris,Kuperman,&Talmud,2007).Imbal-anced dyadic relations often increase conflict pro-pensity and are characterized by“uncertainty and mistrust”(Maoz et al.,2007:104).Therefore,while historical conflict patterns are a result of imbal-anced dyadic relations,they also determine the likelihood of future conflict both within and out-side of a dyad(Beck,Katz,&Tucker,1998).Hence, the dissimilarity in the historical patterns of con-1In international economics,political science,and in-ternational relations,the term“imbalance”is clearly de-fined and used.In business and management,the term “asymmetry”is used with similar meaning.

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flict between nations can serve as a source of infor-mation for firms and impact the perceived threat of opportunism in cross-border contracting.Historical conflict also provides information about the type of antagonism a nation has demonstrated toward other nations.Nations engage in either one-sided or two-sided antagonistic conflicts(Maoz et al.,2007). For firms on the antagonistic side,resource depen-dence and credible commitments create power dis-parities,resulting in their calculating the costs of the safeguards against hazards of opportunism (Williamson,1993).When one nation observes that another displays one-sided antagonistic behavior toward a third nation,the focal nation might assign a higher probability of conflict occurrence to its future relationship with that antagonistic nation. Especially for firms in nation-dyads in which prior within-dyad conflicts are nonexistent or are out-dated,because of the changed conditions of the newly occurring imbalance,a serious void arises, one that inhibits trust,predictability,and reliabil-ity among exchange partners.

Prior to forming alliances,a potential partner has expectations of predictability,reliability,and com-petence about the other(Dyer&Chu,2003),and it has concerns for control,dependence,and vulner-ability to opportunistic behaviors.These expecta-tions and concerns impact its governance choice. While most alliances are susceptible to appropriation hazard,well-crafted contracts safeguard against partner-related hazards and risks,whereas equity alliances require stronger ties and trust as an effi-cient governance mechanism for control.Political hazards also play a key role in governance choice between wholly owned and equity alliance ar-rangements(Henisz,2000a).While conflicts are part of political risk,their prevailing and persisting nature exacerbates the contractual hazards between firms in conflicting nations(Macher&Richman, 2008).Prior relationships and interactions under-pin trust(Gulati,1995);in imbalanced dyadic rela-tionships between nations,where opportunism be-tween nations and firms that belong to those nations is prevalent,firms will observe weaker forms of trust.Trust is built over time by develop-ing shared bonds and values,but when a nation has historically participated in more conflicts,per-ceived threat of opportunism by firms from such a nation might be higher.Hence,these firms will be at a disadvantage in building trust as a substitute for contractual safeguards compared to firms from a na-tion with fewer historical conflicts(Gulati,1995).Effect of Historical Reputation for One-Sided Antagonism on Alliance Type

In the absence of a record of interaction between two nations,given the information asymmetries that result,firms in that nation-dyad will infer what other nations think about the historical context of a particular nation by extrapolating with respect to a third nation.The transitive logic is based on third-party inferences and“updating,”as captured in the saying“The friend of my friend is my friend,the friend of my enemy is my enemy,the enemy of my enemy is my friend,and the enemy of my friend is my enemy”(Crescenzi,2007;Dyer&Chu,2003). Through this extrapolation,firms evaluate the pos-sibility of opportunism(Williamson,1983).When first-hand experience is lacking or limited to de-termining how a perceived imbalance would af-fect nations and firms from those nations,the relations of nations with other nations gains sa-lience(Deutsch,1973).

Therefore,when information about a future part-ner is lacking,and learning more about this partner is prohibitively costly,a referent entity is used as a proxy.The vicarious experiential dimension of ob-served reputation improves informational gaps (Crescenzi,2007).The use of referents increases both the legitimacy of extrapolation and the accu-racy of prediction as a form of learning activity (Deephouse,1996).Therefore,even if an aggressor nation has not displayed aggression to a focal na-tion in the past,it might still bring up notions of greater likelihood of opportunism for the focal na-tion.Just as nations observe a referent nation’s con-flict patterns within the network of nations,firms draw inferences about their potential partners(e.g., Gulati,1998;Terlaak&Gong,2008).Consequently, firms may use prior antagonistic relationships between a partner firm’s nation and other nations as a signal.Inference from that signal relates to whether the partner firm from the antagonistic nation will also be antagonistic toward a focal firm from a nation that is less antagonistic in its prior relations with other nations outside of the dyad.Hence:

Hypothesis2.In a network of nations,as dis-similarity in the degree of prior conflicting re-lationships of nations i versus j with other na-tions in the network increases,the proportion of cross-border equity alliances relative to other types of alliances increases.

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Effect of Recent Reputation for One-Sided Antagonism on Alliance Type

Comparing effects of memory with those of re-cency is of particular interest in studying firms’decisions to enter alliances.Above,the argument was that historically antagonistic nations are more likely to be involved in future conflicts and that firms in nation-dyads from antagonistic nations ex-trapolate their position with respect to network reputational effects.The firms infer direction ac-cordingly and assign higher probabilities to future interfirm conflicts with firms in such dyads.When conflicts are recent,the perceived probability and magnitude of future conflicts are intensified(Maoz, 2009;Schelling,1980).At the nation level,long-term memory(or history)preserves the general level of behavior and forms expectations about po-tential future outcomes,and short-term memory is a direct response to recent behaviors(“priors”; Ward[1982])and influences them.At the individual level,recency often fortifies the priors,making them more powerful and influential(Furnham,1986). Under asymmetric conditions(e.g.,single-sided antagonism),the contractual safeguards against op-portunism and other transaction-specific hazards increase the benefit of alliances compared to hier-archical relations.Among alliances,a higher-com-mitment-seeking alternative will be preferable to a nonbinding arrangement.While the expectation is to favor agreements with lower levels of commitment to lessen risk,the asymmetry in initial conditions within a network,or between the dyad nations,will increase the need for credible commitments as mu-tual deterrents.Regardless of how well the future relationship within a nation-dyad is predicted, given shifting parameters for ideologies and eco-nomic pursuits,firms still seek credibility and pre-dictability from their potential partners.Equity al-liances provide a more reliable and predictable alternative than other alliances,in that parties’in-creasing mutual commitment to an exchange in-creases the costs of defecting and constitutes a re-taliatory threat(Hennart,1988).When information is extrapolated via a referent nation in the network, negative recent information will fortify the negative sentiments of a conflict history,whereas positive recent information will slightly improve a pattern in the network.Thus,firms will seek credible mu-tual commitments in the form of equity alliances when they transact with firms from nations with antagonistic reputations.Hence:

Hypothesis3.As the total number of one-sided conflicts initiated by nations i and j with other nations in a network in a previous year in-creases,the proportion of cross-border equity alliances relative to other types of alliances increases.

Moderating Effects of Learning to Contract Firms’experiences in contracting may mitigate the effects of animosity as they learn not only about a particular governance mechanism but also about how to operate in certain environments.It is well established that firms learn from their prior con-tracting experiences and over time develop con-tracting capabilities(Mayer&Argyres,2004).Firms can develop a contracting capability for entry into foreign markets by learning how the institutional environments of those markets work(Oxley,1997), or they may learn one particular governance mech-anism via experience with a certain type of trans-action(Arikan&McGahan,2010).Given the con-tracting context and conditions an adversarial dyad would present,learning from contracting becomes a salient influence in overcoming the increased threat of opportunism in an antagonistic dyad. Learning from prior cross-border alliances exists at varying degrees along a range from purely contrac-tual relationships to deals that involve equity.Par-ticularly in the context of antagonism,where part-ners face greater ambiguity,equity alliances are more likely to be observed(Anand&Khanna, 2000).Compared to nonequity alliances,equity al-liances are more clearly defined structures that facilitate significantly stronger learning effects (Anand&Khanna,2000;Barkema,Shenkar,Ver-meulen,&Bell,1997).In keeping with this litera-ture,while we expect the number of equity alli-ances in a nation-dyad to be positively related to the prior number of equity alliances,we would expect this effect to be weaker for nonequity alli-ance experience.Hence:

Hypothesis4.Effects of learning to contract through experience are stronger for equity alli-ances than for nonequity alliances. Furthermore,indirect learning effects also exist. Firms may be more likely to form alliances because of vicarious learning from the experiences of their prospective partners(Inkpen&Currall,2004),since learning from the experience of others can lower the prohibitive costs of contractual contingencies, given the changing nature of external environment

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and uncertainties(Mayer&Argyres,2004).Hence, existing alliances within a nation-dyad increase the likelihood of future alliances,as firms display iso-morphic behavior and gain legitimacy by mimick-ing firms that engaged in such alliances.Therefore, firms are more likely to form cross-border equity alliances within a given nation-dyad if organiza-tional legitimacy results(Haunschild,1993;Have-man,1993).

Nations build reputations via their observed ac-tions not only in a focal dyad but also with other dyads within their broader network.Prior alliance experience in a nation-dyad increases the contin-gency planning and haggling costs of transactions (Mayer&Argyres,2004)and augments the ex-pected friction that hampers trust between parties (Nooteboom,Berger,&Noorderhaven,1997).In the context of antagonistic nations,when the perceived threat of opportunism is increased,conditions that foster cooperation are diminished because institu-tional environments will not be conducive to such collaborative activities.The perceptions of in-creased likelihood of opportunism(Henisz&Wil-liamson,1999)and lack of trust between parties (Gulati,1995)will dampen the otherwise positive learning effects seen in equity alliances.

While we maintain that direct and indirect ef-fects of learning to contract through prior experi-ence in equity alliances will increase future equity alliances within a nation-dyad,increased likeli-hood of opportunism and lack of trust in nation-dyads with antagonistic reputations based on much recent one-sided antagonism toward nations out-side the dyad will dampen the conditions that would foster collaboration.Since cross-border eco-nomic activity depends on the institutional envi-ronments of nations as well as their international relations,maintaining legitimacy and safeguarding against opportunism gains salience to firms that would like to form equity alliances.Despite the positive direct and indirect effects of learning to contract,increase in one-sided antagonism toward nations outside of a dyad exacerbates the perceived likelihood of future within-dyad conflict,which in turn impairs the context in which firms learn to contract.Hence:

Hypothesis5.An increased one-sided antago-nistic reputation of the nations in a dyad neg-atively moderates the positive learning effects of prior equity alliance experience.

METHODOLOGY

Sample

We constructed a panel data set of nation-dyads by combining several data sources on(i)verifiable conflicts from1918to2001,(ii)firm-level cross-bor-der alliances,(iii)dyadic trade,and(iv)nation-dyad-specific characteristics.We merged the data sets and considered all possible sovereign nation-dyads.This yielded a square matrix of73times73in the overlap-ping period1988–2000,for conflict and trade data, and full geographic information on sovereign nations. The results are based on the unbalanced sample of 2,480nation-dyads by years,which yielded23,346 nation-dyad observations for1988–2000.

Data

Firm-level alliance data.We used Thomson Reuters SDC Platinum database to identify all firm-level cross-border alliances in1988–2003that had activities in one nation.We restricted these alli-ances to those with two partners from different nations because increasing the number of partners in an alliance increases dyadic measures exponen-tially.Moreover,all dyads in an alliance with more than two nations also have interactions with each other.For example,an alliance involving three firms from Germany,France,and Israel would sug-gest six nation-dyads that could have various de-grees of conflict in and between dyads.We also selected alliances that include activities in a third nation that is different from the partner nations to ensure that the alliances relied less on governmen-tal influences and more on firm-level alliance mo-tivation.Similarly,we excluded alliances whose activities spanned multiple countries,as that would also introduce additional complexity in modeling nation-dyad measures.We also made sure that the ultimate parent firms of partners did not have the same nationality.

Nation-level conflict data.Following Hewitt (2003),we used Dyadic-Level International Crisis Data(version2.0),a part of the International Crisis Behavior Project(ICB)covering the years1918–2001and containing1,228crisis by dyad by year observations.Conflict data are at the dyad level,in dyads in which both nations are part of the ICB-observed interstate system and at least one of the states has threatened the other with a hostile action, which increases the probability of military hostilities in these dyads(Hewitt,2003).One key aspect of this data set is that it identifies the perceptual side of

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conflict.For example,if only one of the nations in a dyad perceives the other as hostile,a crisis is coded as one-sided.2We augmented these data with the Ri-valry Data Set(RDS)and International Crisis Behav-ior Project2(ICB2),which contains overviews of 1,166of these rivalries.The nations coded in the data represent themselves as having sovereign standing at the time of an alliance,and Correlates of War(COW) data corroborate this standing.

Trade,distance,and other variables.For trade, we used the expanded dyadic trade-GDP(v4.1)data (Gleditsch,2002),which include data on dyadic trade,population,gross domestic product(GDP), and real GDP per capita during1948–2000.For distance,we used the CEPII database(Mayer& Zingano,2006),which has different measures of bilateral distances(in kilometers)available for the majority of the nation-dyads we studied(225na-tions),as well as colonial relationships,common language,and ethnicity.Further,we used the COW National Material Capabilities data set(1816–2001; v3.02),which covers six national indicators of ma-terial capabilities:military personnel,military ex-penditure,total and urban(cities with population greater than100,000)populations,iron and steel production(in1,000tons),energy consumption(in 1,000coal-tons),and a composite index score. Social networks.To account for interdepen-dence between nodes and the endogeneity of tie formation,we calculated measures of the structural similarity and centrality of the nations in networks. We utilized UCINET to construct a square matrix of 197nations,based on the cumulative number of dyadic conflicts in1918–87and the cumulative number of firm alliances in1988–2003.Each cell represents the frequency of a dyadic event.We filled empty cells with zeros in both matrices. We present these networks in Figures1–3B,in which the nations are labeled with their COW codes(see the Appendix).Figure1shows the dy-adic conflicts network with the US,UK,Germany, and Russia in its core group(a fitness score of0.40). Figure2,the network of alliances,is12.8times denser than the dyadic conflicts network,which has an average matrix density of0.05and a stan-dard deviation of0.01.This difference is statisti-cally significant at the1percent level(t?6.24). The core group in the alliance network includes the US and Canada(a fitness score of0.97).

We constructed two alliance networks of the re-lationship between the frequency of firm-level alli-ances and nation-dyad conflict:a network of dyads with at least one conflict in1918–87(Figure3A) and a network of dyads without any conflicts in 1918–87(Figure3B).When the two networks are compared,the firm-level alliance network of na-tion-dyads without any conflict in1918–87is6.25 times denser than the one with at least one conflict. This difference in densities is statistically signifi-cant(paired-sample bootstrapped t?5.14,1%sig-nificance level).Similarly,the density of the core group in the network of nation-dyads without any conflict in1918–1987is10times denser than the network of dyads with conflict.

Measures

Dependent variables.To test Hypothesis1,we generated a yearly count variable,the firm-level number of alliances between two nations in a dyad,3and two additional dependent variables to test Hypotheses2–5,calculating the proportion of equity alliances in year t by dividing the number of cross-border firm-level equity alliances by the total number of alliances in a nation-dyad.We calculated the proportion of nonequity alliances similarly.

Independent variables.To test Hypothesis1, which predicts the effect of animosity between two nations,we calculated three measures of animosity. First,political animosity is measured as the cumu-lative number of conflicts in the previous year for the nation-dyad identified in the ICB database, 1918to current year.We also included militarized conflicts such as large-scale military attacks,border conflicts,and war.Second,the relative economic animosity in the previous year is calculated as the yearly imbalance in the imports between two na-tions with respect to each one’s total trade in that

2The RDS uses the COW-MID data set(http://www. https://www.doczj.com/doc/7215184290.html,/)criteria and classifications at dis-pute and participant levels,and covers dispute outcome, form of settlement,fatalities,level of hostility and recip-

rocation,impact on target,and more.We refrained from further classifying types of animosity as it was often problematic to define the root causes or quantify the lingering effects of a conflict after it was officially de-clared resolved(Reuveny&Kang,1996a,1996b).

3We also created an indicator variable that is equal to 1if a nation-dyad has at least one cross-border firm-level alliance and repeated the analysis presented in Table2. The results are consistent for both the probability and the count of alliances.

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year(Reuveny,2000).Trade brings wealth and prosperity,but disproportional distribution of the gains in a dyad leads to interdependence among the nations(Pollins,1989).Disproportional gains give advantages to the nation benefiting more and in-crease the likelihood of future conflicts and aggres-sions(Morrow,1997).These tensions may take the form of political(Gilpin,1981),or military conflict (Mansfield&Pollins,2001).Asymmetries in trade volume are often viewed as aggression by the nation that imports more than it exports in a dyadic relation-ship(Powell,1996).As an import imbalance in-creases,the importing nation is more likely to be perceived as antagonistic(Nijssen&Douglas,2004).4Relative economic animosity ij,t?1

??Imports ij,t?1

Total trade i,t?1??

?Imports ji,t?1

Total trade j,t?1?. Third,to capture the sentiments of populations toward each other(i.e.,consumer behavior,preju-dice,etc.),which are not directly observable in trade and international relations,we predicted the dyadic error term as a proxy for unobservable dyad characteristics that drive conflict between two na-tions in the prior year by estimating the probability of dyadic conflict.5Specifically,conflict reflects anticipation of reaction from the other nation in a

4The order of the nation subscripts corresponds to the directionality of the imports,the first being the exporter and the second being the importer.We also created an-other measure,by dividing instead of subtracting.Al-though the sample decreases to1,913clusters at the dyad level(because of the unidentifiable fraction of0divided by0)yielding14,299observations,the results do not change qualitatively,and the coefficients of the indepen-dent variables in model6of Table2are as follows:cumulative conflict:b??0.31,s.e.?0.10,t?–3.17, p?.002;elasticity of economic animosity:b?0.11, s.e.?0.32,t?0.33,p?.74;and estimated dyadic error term as a proxy for the unobservable dyad characteristics that drive conflict in the previous year,b??1.04,s.e.?0.21,t?–4.92,p?.001.This specification also pro-vides a robustness check for sample size;results are even stronger when the sample is decreased by38.75percent, to14,299from23,346(as reported in Table2).

5Analysis is available from the authors.

FIGURE1

Network of Cumulative Conflict between Nation-Dyads,1918–87

Density matrix

Core

Peri

p hery

Core Periphery 10.50.422 0.422 0.034

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Arikan and Shenkar

dyad,while taking trade as a given;6“conflict is thus in the error term”(Stein,2003:16).Further-more,we expect unobservable drivers of conflict in a prior period to influence future trade activities such as cross-border firm-level alliance.

To test Hypothesis 2,we constructed the conflict network of all nation-dyads in our data using UCINET 6.0and calculated the dissimilarity in the degree of prior conflicting relationships of nation i versus j with other nations in a network over the years 1918–87as the Euclidian distance between them (Benson,2004).Euclidian distance represents the relationship between nodes in terms of their

comparative position in the sociomatrix in a par-ticular social space (Cronbach &Gleser,1953).In our context,for a nation dyad i and j ,we measure dissimilarity in the degree of prior i versus j con-flicts with other nations in a network using the Euclidian distance formula,the squared difference of the strength of the first nation’s ties to a third nation from the strength of the second nation’s ties to the third nation,and then summed for all nations other than the dyad nations in the network.If the dissimilarity measure in a dyad is zero,then the two nodes are structurally identical.

To test Hypothesis 3,which estimates the effect of antagonistic reputation on the proportion of equity alliances,we used the classification of con-flicts in the ICB database,because currently an-tagonistic nations are more likely to be involved in future conflicts (Beck et al.,1998).We mea-

6

Governments encourage trade between conflicting nations in the hopes of increasing costs of future con-flicts.We observe a positive correlation between the cu-mulative conflict and observed trade levels (Stein,2003).

FIGURE 2

Network of Cumulative Cross-Border Strategic Alliances between Nation-Dyads,1988–2003

Density matrix

Core Peri p hery Core

Periphery

1,619 20.6510.182

20.651

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Academy of Management Journal

sured the cumulative antagonism in a nation-dyad by adding up the total number of conflicts for nations i and j in which at least one of the two nations was classified as the initiator in a conflict with a third nation outside of the dyad,excluding the conflicts in this dyad.

To test Hypothesis 4,we calculated a count vari-able,total number of equity alliances between na-tions i and j in the previous year .To test Hypothesis 5,we multiplied total number of equity alliances between nations i and j in the previous year by the variable of cumulative antagonism in a nation-dyad in a previous year.

Control variables.We included three types of con-trol variables in our empirical models:nation-specific,dyad-specific,and other exogenous variables.

Our nation-specific control was the yearly na-tion-specific composite index score for material ca-pabilities.This is a statistically significant predic-tor of trade measured as exports from the first nation to the second nation in a dyad.

Dyad-specific controls were three dichotomous variables (coded 1if yes,0otherwise):(i)interstate interactions between two nations are more likely if they are contiguous ,(ii)share a common lan-guage that is spoken by at least by 9percent of the population ,and (iii)have at least one bilat-eral agreement .

Geographic distance also influences the interac-tions between nations.The logged value of distance in kilometers between the capital cities of the nations in a dyad was calculated,as the geographic distance between nations does not typically change over short periods of time.Furthermore,we created a trend vari-able by subtracting 1987from the current year to account for the increased data coverage of firm-level alliances.Additionally,we included year dummies to account for any year-specific effects.

To isolate the effect of and control for the yearly dyadic trade level,we developed two measures (Helpman,Melitz,&Rubinstein,2008):(i)pre-dicted level of trade,measured (in 1996US dollars)as exports in a previous year from the first nation to the second nation in a dyad and (ii)unobserved dyadic characteristics that determine the previous-year level of exports from the first nation to the second nation in a dyad.These predicted values are obtained from the simultaneous equations es-timation method,as both conflict and trade are more likely to be determined simultaneously by

FIGURE 3A

Network of Cumulative Cross-Border Strategic Alliances in 1988–2003between Nation-Dyads

with at least One Conflict in 1918–87

Density (matrix average) = 0.0040 Standard deviation = 0.0630 Simple Core/Periphery Model Final ?tness: 0.153 Density matrix Core Periphery Core 0.031 0.000 Periphery 0.000 0.000

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overlapping variables (Timpone,2003).This si-multaneous equations estimation of the dyadic trade levels and the probability of dyadic conflict included additional nation-specific variables,and dyad-specific variables,such as sharing a common official language (1if two nations have the same language,0otherwise),and the logged value of the distance in kilometers between the most populated cities of the two nations in the dyad (available upon request).We also controlled for the economic imbalance in the previous year by calculating the dyadic ratio of relative real GDP per capita in percentiles,as a proxy for asymmetrical power relationship between na-tions,which increases the likelihood of trade agreements (Genna,2010).Empirical Methodology

Isolating the impact of animosity on the occur-rence and frequency of firm-level alliances poses six challenges in empirical modeling:(i)nation-dyads that have had historical conflicts are more likely to have future conflicts,(ii)firm-level alli-ances need to account for the causality and/or simultaneity in dyadic economic activity and con-flict,(iii)dyadic trade and conflict are inherited in the case of firm-level alliances since they are a form of dyadic trade,(iv)network-level analysis needs to take into account heteroskedasticity between dyads due to overlap of nations across dyads and time-specific sources of dependence among observa-tions,(v)excessive numbers of zeros in dyadic variables for alliances and exports cause overdis-persion in variance,and (vi)dyadic conflicts are rare events.

We extrapolate the effects of the above chal-lenges to three econometric issues—endogeneity bias,sample selection bias,and multiple sources of heteroskedasticity—and address the concerns as follows:We estimated the probabilities of con-flict and the level of trade in a nation-dyad sep-arately as well as simultaneously to address the sample selection and endogeneity biases.We used two variables,the predicted level of dyadic trade and the predicted standardized error term as a proxy for unobservable dyad characteristics that impact trade levels.Additionally,we in-cluded the probability of conflict in our main estimation models to test our hypotheses.

FIGURE 3B

Network of Cumulative Cross-Border Strategic Alliances in 1988–2003between Nation-Dyads

without Any Conflict in

1918–87

Density (matrix average) = 0.0246Standard deviation = 0.1548Simple Core/Periphery Model Final ?tness: 0.541Density matrix Core Periphery Core 0.312 0.033 Periphery 0.033 0.000

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We report the results of estimating logistic re-gression models to test Hypothesis1and tobit regression models for Hypotheses2–4.We also conducted robustness checks with alternative models and specifications to evaluate the impact of rare event bias,overdispersion bias,dyadic trade level,and the indicator variable of dyadic conflict.Therefore we employed(i)rare-events logistic regression for Hypothesis1and(ii)zero-inflated models of negative binomial(ZINB)and Poisson regressions in which the dependent vari-ables are the number of alliances for Hypothesis 1,and the number of equity alliances for Hypoth-eses2–4.By employing zero-inflated models,we were able to include a simultaneous estimation of observing a value of zero,which also addresses sample selection concerns that would arise if hypotheses were tested only by including the subsample of nonzero observations(Winkel-mann,2008).We report the results of standard-ized estimations.To address the econometric problem of heteroskedasticity due to noninde-pendence of the dyadic observations embedded in a network and tracked over multiple years,we used the Stata code for the three-way clustering of standard error terms in nonlinear estimations of Poisson,rare-events logit,negative binomial, ZINB(Cameron&Tivendi,1998;Long&Freeze, 2001),and zero-inflated-Poisson models.The main results hold across all specifications,and we report the results of ZINB estimation.Our event count model for Hypothesis1is:

The dependent variable for Hypotheses2–5 captures the ratio of equity alliances over total number of alliances and the ratio of nonequity alliances over total number of alliances.Since these measures have a lower bound at0and an upper bound at1with corner solutions due to a maximization process rather than unobservable data problems,we use Tobit analysis (Wooldridge,2002).Tobit analysis is sensitive to normality assumptions,and the dependent vari-able is nonnormal.We checked the ratio of equity alliances to nonequity alliances,which is also nonnormal,with left-skewness(significant test statistic of10.83[p?.0001]where the null is normally distributed error terms)to identify out-liers.We excluded extreme outliers(determined via the“iqr”command)of this ratio(values greater than4)to eliminate nonnormality.The main model for Hypotheses2–5was estimated using Tobit regression,given that the dependent variable y i,t is a proportion of equity or nonequity alliances between0and1.

y ij,t??Ratio of firm-level equity alliances over

total number of alliances in a nation-dyad?ij,t0.

RESULTS

Table1provides descriptive statistics for the variables of interest.Results pertaining to the test of Hypothesis1are presented in Table2.Overall re-sults provide support for Hypothesis1,which stip-ulates a negative relationship between dyadic

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Arikan and Shenkar

T A B L E 1D e s c r i p t i v e S t a t i s t i c s

M e a n s .d .12345678910111213141516171819202122

1.N u m b e r o f a l l i a n c e s b e t w e e n i a n d j i n c u r r e n t y e a r 0.030.95

2.N u m b e r o f n o n e q u i t y a l l i a n c e s b e t w e e n i a n d j i n c u r r e n t y e a r 0.020.62.92

3.N u m b e r o f e q u i t y a l l i a n c e s b e t w e e n i a n d j i n c u r r e n t y e a r 0.020.4

4.84

.56

4.P r o p o r t i o n o f e q u i t y a l l i a n c e s b e t w e e n i a n d j i n c u r r e n t y e a r 0.590.42?.13?.26

.115.P r o p o r t i o n o f n o n e q u i t y a l l i a n c e s b e t w e e n i a n d j i n c u r r e n t y e a r 0.410.42.13

.26?.11?1.006.C u m u l a t i v e n u m b e r o f c o n f l i c t s b e t w e e n i a n d j i n p r e v i o u s y e a r 0.020.26.08

.03.13.10?.107.R e l a t i v e e c o n o m i c a n i m o s i t y b e t w e e n a n d j i n p r e v i o u s y e a r 0.000.02?.09?.09?.08

.06?.06?.048.E s t i m a t e d d y a d i c e r r o r t e r m a s p r o x y f o r u n o b s e r v a b l e c h a r a c t e r i s t i c s t h a t i m p a c t d y a d i c c o n f l i c t i n p r e v i o u s y e a r 0.920.20.07

.07.05?.16.16?.03?.059.C o n f l i c t n e t w o r k m e a s u r e o f d i s s i m i l a r i t y i n d e g r e e o f c o n f l i c t i n g r e l a t i o n s h i p s o f i v e r s u s j w i t h o t h e r n a t i o n s i n n e t w o r k ,1918–877.817.16.08.06.08?.06.06.11?.16.06

10.T o t a l n u m b e r o f o n e -s i d e d c o n f l i c t s i n i t i a t e d b y i a n d j w i t h o t h e r n a t i o n s i n n e t w o r k i n p r e v i o u s y e a r 0.060.84.08

.03.14.09?.09.62?.02.04.13

11N u m b e r o f e q u i t y a l l i a n c e s b e t w e e n i a n d j i n p r e v i o u s y e a r 0.020.46.76

.56.83?.03.03.13?.08.05.08

.13

12.N u m b e r o f n o n e q u i t y a l l i a n c e s b e t w e e n i a n d j i n p r e v i o u s y e a r 0.020.61.86

.92.53?.19.19.03?.09.08.06

.03

.58

13.E s t i m a t e d e x p o r t s f r o m i t o j i n p r e v i o u s y e a r 0.130.65.23.19.20?.03.03.36?.11.29.22.60.20.1914.E s t i m a t e d d y a d i c e r r o r t e r m a s p r o x y f o r u n o b s e r v a b l e d y a d i c c h a r a c t e r i s t i c s t h a t i m p a c t t r a d e f r o m i t o j i n p r e v i o u s y e a r 0.040.03.11

.09.10.00.00.20?.02.47.05

.33

.10.09.45

15.D y a d h a s a t l e a s t o n e b i l a t e r a l n a t i o n a l l i a n c e i n p r e v i o u s y e a r a

0.990.11?.01

.00?.02?.09.09?.06.07

?.07?.12?.11?.02.00?.22?.13

16.L o g g e d r a t i o o f d y a d i c n a t i o n a l e n e r g y c o n s u m p t i o n o v e r u r b a n p o p u l a t i o n i n p r e v i o u s y e a r 18.413.850.090.070.09

0.02?0.020.080.06?0.040.430.100.090.070.280.01?0.11

17.C o m p o s i t e i n d e x s c o r e f o r i ’s m a t e r i a l c a p a b i l i t i e s 0.000.02.17

.14.16?.14.14

.12?.38

.03

.47

.14

.17

.14

.29

.12

?.10

.09

18.C o m p o s i t e i n d e x s c o r e f o r j ’s m a t e r i a l c a p a b i l i t i e s 0.010.02.12

.09.12?.02

.02

.05

.12

?.07.43.08.12.09.10.00

?.06

.55

.00

19.L o g g e d d i s t a n c e b e t w e e n c a p i t a l c i t i e s o f i a n d j i n k i l o m e t e r s 8.710.79?.03?.04?.01

.01

?.01?.11

.07

?.55?.06?.09?.01?.04?.13?.22

.21

.02

.02

.08

20.D y a d s h a r e s b o r d e r a

0.020.15.11.12.06?.05.05.17?.04.16.03.15.06.13.50.32?.22.04.04.03?.3421.D y a d s h a r e s l a n g u a g e s p o k e n b y a t l e a s t 9p e r c e n t o f e a c h p o p u l a t i o n a

0.130.33.06

.06.03

?.09

.09

.04?.13

.07

.00

.01

.03

.06

.08.18

?.01?.02

.07.03?.14.12

22.T r e n d b

7.443.97.01.01

.00

?.22

.22

.00.01

.00

.00

.00

.01

.01

.03?.01

?.04?.03?.02?.01?.01.00?.01

a

C o d e d 1f o r y e s ,0o t h e r w i s e .

b

Y e a r -1988.

T A B L E 2W i t h i n -D y a d C o n f l i c t a n d t h e N u m b e r o f A l l i a n c e s i n a N a t i o n -D y a d

V a r i a b l e s

M o d e l 1

M o d e l 2M o d e l 3M o d e l 4M o d e l 5M o d e l 6

N u m b e r o f A l l i a n c e s i ,j ,t

D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a

C u m u l a t i v e n u m b e r o f c o n f l i c t s b e t w e e n i a n d j i n p r e v i o u s y e a r (H 1)?0.010.05?0.09***

0.03

R e l a t i v e e c o n o m i c a n i m o s i t y b e t w e e n i a n d j i n t h e p r e v i o u s y e a r (H 1)?0.054?0.03

0.010.06

E s t i m a t e d d y a d i c e r r o r a s p r o x y f o r u n o b s e r v a b l e c h a r a c t e r i s t i c s t h a t i m p a c t d y a d i c c o n f l i c t i n p r e v i o u s y e a r (H 1)?0.79***0.15?1.09***0.17

E s t i m a t e d e x p o r t s f r o m i t o j i n p r e v i o u s y e a r 0.80**

0.260.820.420.83*0.410.83*0.420.84*

0.33

0.87***

0.26

E s t i m a t e d d y a d i c e r r o r t e r m a s p r o x y f o r u n o b s e r v a b l e d y a d i c c h a r a c t e r i s t i c s t h a t i m p a c t t r a d e f r o m i t o j i n p r e v i o u s y e a r ?1.15**0.39

?1.17*0.57?1.17*0.57?1.18*0.56

?0.96

0.49

?0.87***

0.26

L o g g e d d i s t a n c e b e t w e e n c a p i t a l c i t i e s o f i a n d j i n k i l o m e t e r s ?0.070.19?0.070.31?0.070.3?0.080.29?0.10.26?0.160.21

D y a d s h a r e s b o r d e r a

1.47**0.521.421.171.411.151.451.240.730.930.40.97D y a d s h a r e s l a n g u a g e s p o k e n b y a t l e a s t 9p e r c e n t o f e a c h p o p u l a t i o n a

0.180.37

?1.47***

0.520.220.53?1.46*0.720.20.6?1.50*0.70.260.5

?1.420.75

0.190.43

?1.18*0.5

?0.010.34

?1.31**0.47

T r e n d b

?0.110.21?0.050.03?.050.03?0.050.03?0.060.03?0.060.03D y a d h a s a t l e a s t o n e b i l a t e r a l n a t i o n a l a l l i a n c e i n p r e v i o u s y e a r 0.730.420.680.550.690.580.690.60.60.380.770.46

L o g g e d r a t i o o f d y a d i c n a t i o n a l e n e r g y c o n s u m p t i o n o v e r u r b a n p o p u l a t i o n i n p r e v i o u s y e a r ?2.01***0.32?2.05***0.59?2.06***0.6?2.02***0.61?1.72***0.52?0.090.06

C o m p o s i t e i n d e x s c o r e f o r i ’s m a t e r i a l c a p a b i l i t i e s 0.42***0.04?0.10.070.41***0.07?0.110.060.42***0.08?0.110.060.42***0.07?0.110.060.37***0.05?0.110.060.40***0.070.20.15

C o m p o s i t e i n d e x s c o r e f o r j ’s m a t e r i a l c a p a b i l i t i e s 0.46***0.070.31*0.120.46***0.090.320.160.47***0.130.330.180.46***0.090.310.170.41***0.090.180.150.49***0.1

Y e a r d u m m i e s (1989–2001)

n .s .

(C o n t i n u e d )

T A B L E 2(C o n t i n u e d )

V a r i a b l e s

M o d e l 1

M o d e l 2M o d e l 3M o d e l 4M o d e l 5M o d e l 6

N u m b e r o f A l l i a n c e s i ,j ,t

D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a N u m b e r o f A l l i a n c e s i ,j ,t D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a

N u m b e r o f A l l i a n c e s i ,j ,t

D u m m y f o r Z e r o A l l i a n c e s i ,j ,t a

L o g g e d ?2

0.030.420.170.530.180.540.140.64?0.040.48?0.250.53C o n s t a n t ?1.973.014.21***0.51?2.80***0.624.22***0.52?2.83***0.594.20***0.55?2.790.644.22***0.52?3.08***0.523.86***0.46?3.43***0.53.59***0.44E m p i r i c a l m o d e l

Z e r o -i n f l a t e d n e g a t i v e b i n o m i a l r e g r e s s i o n ,r o b u s t ,o n e -w a y c l u s t e r e d e r r o r Z e r o -i n f l a t e d n e g a t i v e b i n o m i a l r e g r e s s i o n ,t h r e e -w a y c l u s t e r e d e r r o r

Z e r o -i n f l a t e d n e g a t i v e b i n o m i a l r e g r e s s i o n ,t h r e e -w a y c l u s t e r e d e r r o r Z e r o -i n f l a t e d n e g a t i v e b i n o m i a l r e g r e s s i o n ,t h r e e -w a y c l u s t e r e d e r r o r

Z e r o -i n f l a t e d n e g a t i v e b i n o m i a l r e g r e s s i o n ,t h r e e -w a y c l u s t e r e d e r r o r

Z e r o -i n f l a t e d n e g a t i v e b i n o m i a l r e g r e s s i o n ,t h r e e -w a y c l u s t e r e d e r r o r

?2

368.36***582.12***595.34***600.32***901.24***1,062.79***L o g -l i k e l i h o o d ?2,059.12?2,071.87?2,070.27?2,069.46?1,996.3?1,975.17L o g -l i k e l i h o o d o f t h e n u l l ?2,363.94

?2,363.94

?2,363.94?2,363.94

?2,324.32

?2,324.32

l i k e l i h o o d -r a t i o a g a i n s t t h e n u l l 609.64***

584.14***

584.66***584.38***

656.04***

698.3***

d f 21

999912L i k e l i h o o d r a t i o a g a i n s t 23.2?

4.83**151.14***

193.4***

d f 1113N u m b

e r o

f o b s e r v a t i o n s 23,346

23,346

23,346

23,346

20,906

20,906

N u m b e r o f z e r o o b s e r v a t i o n s 22,870

22,870

22,87022,870

22,870

22,870

N u m b e r o f c l u s t e r s (n a t i o n -d y a d )2,480

N u m b e r o f c l u s t e r s (n a t i o n i ,n a t i o n j ,y e a r )

73,53,1173,53,1173,51,1173,53,1173,53,11

a

C o d e d 1f o r y e s ,0o t h e r w i s e .b

Y e a r -1988.?p ?.10*p ?.05**p ?.01***p ?.001

conflict at the national level and the likelihood of observing cross-border alliances at the firm level.7Model 1is the base model with all control vari-ables,including the year dummies,which are statistically nonsignificant.In model 2,we remove the year dummies.The overall model is statistically significant (p ?.001).We explain the results in terms of the odds ratios:Holding all else fixed,a one-unit increase in the estimated level of exports from the first nation to the second one increases the number of firm-level alliances 2.23times (e 0.8),or 123percent (p ?.01).Conversely,a one-unit increase in the estimated unobservable dyadic characteristics that impact trade in the previous year decreases the number of alliances 3.16times (e 1.15),or 216percent (p ?.01).If the nations in a dyad have a common border,the number of alliances increases 4.35times (e 1.47),or 335percent (p ?.01).If the dyad nations have a common language spoken by at least 9percent of the population,the odds of observing no alliances decrease 0.23times (e ?1.47),or 77percent (p ?.01),with no statistically significant effect on the number of alliances.We capture the material capabilities of nations with a comparative ratio for prior year energy consumption per urban person and composite index scores for both nations.As the ratio of dyadic national energy consumption over urban population in the previous year increases by one unit,the number of alliances decreases 13.4times (e –2.01),or 76.6percent (p ?.001).If the composite material capabilities in-dex for nations i and j is increased separately by one unit,the number of alliances increases 1.52times (e 0.42),or 52percent (p ?.001),and 1.56times (e 0.46),or 56percent (p ?.001),respectively.Removing the year dummies makes the estimated level of exports and sharing a border not significant.

The three independent variables,cumulative num-ber of conflicts,relative economic animosity,and un-observable dyadic characteristics that drive conflict,were individually included in models 3–6.In model 3,the cumulative number of dyadic conflicts is sta-tistically insignificant,and this variable neither im-proves the model significantly (likelihood ratio ?3.2,p ?.1)nor changes any of the coefficients in the base model qualitatively.This result is consistent with our thinking that the observed number of cumulative conflicts is not as straightforward a proxy with which to capture national dyadic animosity.In model 4,relative economic animosity,which measures the im-

balance between the nations in a dyad in terms of their dependence on imports from each other as a ratio of total trade,is included.The coefficient of this variable is negative and weakly significant (p ?.1).A one-unit increase in economic animosity decreases the number of alliances 0.95times (e –0.054),or 5per-cent.This variable decreases the significance levels of the coefficients for common language spoken by at least 9percent of the population (p ?.1)and esti-mated level of exports from first nation to the second one in the previous year (p ?.05).As hypothesized,relative economic animosity based on the depen-dence on imports from another nation decreases the odds of observing firm-level cross-border alliances between these nations.

In model 5,we include the estimated dyadic error term as a proxy for unobservable characteris-tics impacting prior-year dyadic conflict.The coef-ficient of this variable is negative and statistically significant (p ?.001).Among the three independent variables that account for dyadic animosity,this vari-able has the highest statistical significance.A one-unit increase in the proxy decreases the odds of ob-serving alliances 0.45times (e –0.79),or 55percent.Model 6combines all three explanatory variables used to test Hypotheses 1.While cumulative num-ber of dyadic conflicts becomes highly significant (p ?.001),relative economic animosity becomes statistically insignificant,as would be expected given its weak explanatory power in model 4.The coefficient of the estimated dyadic error term as a proxy for unobservable characteristics impacting prior-year dyadic conflict is slightly increased and has high statistical significance (p ?.001).

Results of tests of Hypotheses 2–5are presented in Tables 3and 4.First,we consider the results for equity alliances (Table 3).Models 1–6,estimated by Tobit regression with robust standard errors clustered at the nation-dyad level,provide strong support for Hypotheses 2–5.Model 1,the baseline including control variables,is statistically signifi-cant overall (p ?.001),and the pseudo-R 2is 14percent.As the gap between the percentiles of logged real GDP per capita increases by one unit,the proportion of equity alliances relative to total alliances increases by 35.6percent (p ?.05).Sim-ilarly,historical conflict 1918–87between nations i and j increases this proportion by 16.7percent (p ?.05).Distance between the capital cities of nations i and j is positively related to the propor-tion of equity alliances to total alliances with weaker statistical significance (p ?.1).

7

The results hold when we use a dummy variable for at least one cross-border alliance as well.

20131533

Arikan and Shenkar

T A B L E 3R e p u t a t i o n f o r A n t a g o n i s m ,L e a r n i n g t o C o n t r a c t ,a n d P r o p o r t i o n o f E q u i t y A l l i a n c e s

V a r i a b l e s

M o d e l 1

M o d e l 2M o d e l 3M o d e l 4M o d e l 5M o d e l 6

C o n f l i c t n e t w o r k m e a s u r e o f d i s s i m i l a r i t y i n d e g r e e o f c o n f l i c t r e l a t i o n s h i p s o f i v e r s u s j w i t h o t h e r n a t i o n s i n t h e n e t w o r k ,1918–87(H 2)0.105*0.0430.073?0.0380.066?

0.038

T o t a l n u m b e r o f o n e -s i d e d c o n f l i c t s i n i t i a t e d b y i a n d j w i t h o t h e r n a t i o n s i n n e t w o r k i n p r e v i o u s y e a r (H 3)0.008**0.0030.006*0.0030.011***0.003

N u m b e r o f e q u i t y a l l i a n c e s b e t w e e n i a n d j i n p r e v i o u s y e a r a (H 4)0.024***0.0060.021***0.0060.030**

0.01

N u m b e r o f e q u i t y a l l i a n c e s b e t w e e n i a n d j i n p r e v i o u s y e a r ?t o t a l n u m b e r o f o n e -s i d e d c o n f l i c t s i n i t i a t e d b y i a n d j w i t h o t h e r n a t i o n s i n n e t w o r k i n p r e v i o u s y e a r (H 5)?0.001*

0.0004

L o g g e d d i s t a n c e b e t w e e n c a p i t a l c i t i e s o f i a n d j i n k i l o m e t e r s 0.135?

0.0730.118?0.07

0.127?0.0710.1

0.07

0.086

0.066

0.087

0.066

D y a d s h a r e s b o r d e r 0.2040.2350.2190.2190.2290.2330.1160.2260.1570.2130.1230.216D y a d s h a r e s l a n g u a g e s p o k e n b y a t l e a s t 9p e r c e n t o f e a c h p o p u l a t i o n ?0.040.083?0.058

0.079

0.0030.089?0.0410.075

?0.022

0.078

?0.028

0.076

T i m e t r e n d ?0.039***0.009?0.033***0.009?0.041***0.009?0.041***0.009

?0.038***0.008?0.038***0.008P r e d i c t e d n u m b e r o f a l l i a n c e s c 0.018*0.0070.015*0.0070.0120.0090.007?0.0030.0020.004?0.0010.005C o n s t a n t 0.469***0.0910.1770.1430.467***0.0910.463***0.0870.261*0.1310.260*0.128S i g m a 0.388***0.0330.382***0.0320.380***0.0340.370***0.030.361***0.0310.357***0.03E m p i r i c a l m o d e l T o b i t r e g r e s s i o n ;r o b u s t ,o n e -w a y c l u s t e r e d e r r o r s T o b i t r e g r e s s i o n ;r o b u s t ,o n e -w a y c l u s t e r e d e r r o r s T o b i t r e g r e s s i o n ;r o b u s t ,o n e -w a y c l u s t e r e d e r r o r s T o b i t r e g r e s s i o n ;r o b u s t ,o n e -w a y c l u s t e r e d e r r o r s T o b i t r e g r e s s i o n ;r o b u s t ,o n e -w a y c l u s t e r e d e r r o r s T o b i t r e g r e s s i o n ;r o b u s t ,o n e -w a y c l u s t e r e d e r r o r s F 4.74***7.18***9.4***7.68***10.88***13.51***R 2(p s e u d o )0.140.170.160.20.230.24L o g -l i k e l i h o o d ?154.39?148.96?150.75?143.6?138.18?135.64L o g -l i k e l i h o o d o f n u l l ?179.475?179.475?179.475?179.475?179.475?179.475l i k e l i h o o d -r a t i o ?2a g a i n s t n u l l 50.17***61.03***57.45***71.75***82.59***87.67***d f 566689L i k e l i h o o d -r a t i o ?2a g a i n s t 110.86***7.28**21.58***32.42***37.5***d f (p r o b ??2)1(0.001)

1(0.007)

1(?0.001)

3(?0.001)

4(?0.001)L i k e l i h o o d -r a t i o ?2a g a i n s t 55.08*d f (p r o b ??2)1(0.024)N u m b e r o f o b s e r v a t i o n s 262262262262262262N u m b e r o f c l u s t e r s 747474747474L e f t -c e n s o r e d o b s e r v a t i o n s ?0104104104104104104R i g h t -c e n s o r e d o b s e r v a t i o n s ?10

00

a

E x t r e m e o u t l i e r s (i f e q u i t y /n o n e q u i t y a l l i a n c e s ?4)a r e e x c l u d e d .b

Y e a r -1987.c F r o m T a b l e 2,m o d e l 6.?p ?.10*p ?.05**p ?.01***p ?.001

As stated in Hypothesis2,the marginal effect of our conflict network measure of dissimilarity be-tween the degree of1918–87conflict between i and j and that with other nations in the network during 1918–87on the proportion of equity alliances to total alliances is11percent(p?.05).Dyads with nations that differ significantly in their historical con-flict levels are expected to have a higher proportion of equity alliances.Including this variable improves overall significance of model1at.001percent,with a chi-square of10.86.This provides strong support for Hypothesis2as presented in model2.

As stated in Hypothesis3,the positive marginal effect of the total number of one-sided conflicts initiated by nations i and j with other nations in a network in a previous year on the proportion of eq-uity alliances to total alliances is0.8percent(p?.01). Nations that have been antagonistic outside of their focal dyad are expected to have more equity alliances in the focal dyad.Including this variable improves the overall significance of model1at.01percent, with a chi-square of7.28.This strongly supports Hy-pothesis3.

As stated in Hypothesis4,the effect of the num-ber of prior-year equity alliances between nations i and j is positive and statistically significant(p?.01).A one unit increase in the proportion of equity alliances over total alliances in a previous year increases the proportion of equity alliances by (e0.03)or3percent(p?.01).As hypothesized,the variable for learning effects of prior equity alliances is positive,which is consistent with Hypothesis4. Comparing this result with the results of the same specification with proportion of nonequity alli-ances as dependent variable(Table4)shows that the number of prior-year nonequity alliances be-tween i and j is statistically insignificant and con-tributes no additional explanatory power to the base model.Overall,comparing the coefficients of number of prior equity alliances(Table3)and number of nonequity alliances(Table4)suggests more learning from the equity alliances.This result provides strong support for Hypothesis4.

As stated in Hypothesis5,the interaction effect of the number of equity alliances between i and j in a previous year and the total number of one-sided con-flicts initiated by nations i and j with other nations in a network in a previous year is negative and statisti-cally significant(p?.05).The positive average mar-ginal effect of the prior number of equity alliances is dampened by conflicts initiated by0.1percent(p?.05).This result suggests that increased reputation for antagonism decreases the positive learning effect of prior equity alliance experience.Overall,results pro-vide strong support for Hypothesis5.

Robustness Checks

Sample selection bias.Because the majority of trade was observed in a small percentage of the nation-dyads,including only nation-dyads that have a trade relationship could be a problem. Hence,we estimated a gravity model of trade(Tin-bergen,1962),using ZINB because of overdisper-sion in the variance as a result of high frequency of zeros(Winkelmann,2008).We used the following covariates:dyadic conflict,logged GDPs,logged distance,one-year lagged variables of total trade ratio,relative ratio of national military expenditures to total trade,relative ratio of national military per-sonnel to total population,and nonlinear effects of distance and GDP(Maoz,2009).The main variables identified in the gravity model of trade explain20 percent of the variation,excluding the year dummies that are included in the main analysis. Endogeneity bias.We tested the impact of con-flict on the occurrence and frequency of cross-bor-der alliances and equity alliances.Given that both trade and conflict are determined by the same co-variates and also cause each other,isolating the impact of conflict requires careful and comprehen-sive empirical modeling(Martin,Mayer,&Thoe-nig,2008).On the one hand,trade increases con-flict cost and serves as a deterrent;on the other hand,increased trade between proximate nations increases likelihood of conflict.Also,trade and conflict among nations are both endogenously de-termined since unobservable nation-dyad charac-teristics may be driving the number of conflicts and trade level(Timpone,2003).

Hence,we utilized a two-stage procedure to correct for endogeneity bias.First,we estimated the proba-bility of conflict and level of dyadic trade measured as separate equations for calibration.Second,we gen-erated simultaneous equation estimations of these two equations.The R2for the models that estimate the probability of dyadic conflict ranged between40 and48percent.Additionally we estimated dyadic trade,measured as level of exports from the first na-tion to the second in a dyad,as a stand-alone estima-tion with covariates identified in previous research and obtained21percent explanatory power.This ap-proach provides further confidence about the covari-ates identified,and allowed us to simultaneously pre-dict two control variables,(i)error terms as a proxy for the unobservable dyadic characteristics that im-pact trade and(ii)level of trade,export

è

ij,t

20131535

Arikan and Shenkar

中国文化概论知识点总结

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第8题东晋以后,佛教涅学的代表人物是() A. 道安 B. 慧远 C. 道生 D. 僧肇 【正确答案】 C 本题分数1分 第9题我国火药的发明最迟是在()。 A. 唐代 B. 北宋 C. 南宋 D. 元代 【正确答案】 A 本题分数1分 第10题中国封建社会后期的文化正宗是() A. 道家学说 B. 魏晋玄学 C. 宋明理学 D. 阴阳五行说 【正确答案】 C 本题分数1分 第11题在我国治理自然环境方面最早做出不懈努力的人是() A. 唐尧 B. 虞舜 C. 夏禹 D. 商汤 【正确答案】 C

2014年10月份中国文化概论知识点

1、文化被划分成哪两个层次?两个层次的区别是什么?答:①上层文化和底层文化。②上层文化指宫廷文化与上层文人所创造、拥有的文化;底层文化指民间文化,即不依赖于统治阶级的广大人民及其精英人物所创造、拥有的文化。1、简述地理环境是人类存在和文化创造的先决条件。答:①生活在一定地理范围中的人群,必须依赖自然界提供他们的地理条件,从而展开其文化创造历程;②了解一个文化的总体特征,从地理方面进行观察是十分必要的;(③了解文化时所作的地理观察,必须是历史的,文化与地理互动的;④地理对人文的影响,有许多复杂的中介内容。 2、简述中国古代文化的基干。答:了解中国文化的基干,必须涉及先秦区域文化的发展。其为:源于齐鲁的儒家文化;源于三晋的法家文化;源于南楚的道家及楚辞文学。后经融汇,成为中国文化的基干。 3、简述中国文化史上的山西居“天下形势”。答:①山西高原的北部与蒙古高原相接,故而是内迁的北方民族进入中原地区的要路。②太行山脉中的某些断裂处,又可以直通华北,故而历来有山西居“天下形势”之说。 4、请以实例说明典范人物对特定地域文化特色的影响。答:典型人物潜移默化的影响也可以带出特定地域的文化特色。任何人都有自己的出生地,而且任何人对此都会有所觉知,因此,产生乡土意识。例如,桐城人以文章扬名,是因为苞、姚等人的影响所致。浙东重史学,是因为黄宗羲的影响所致。徽州尚经术,是因为戴震的影响所致。 5、为什么说华北平原是中国文化的又一摇篮?答:⑴华北平原有黄河、海河两大水系。利于舟楫之便和人的交流。⑵东部有泰沂山地,有利于人们的文化创造。⑶该地区历来就是发达的农业区,有利于农业文明的创造与发。⑷该地区在很长时期内人口稠密。 6、统一是中国自古以来占主导倾向的追求,其表现有哪些?答:①自有人群以来就相互交流;②甲骨文中有“四方”的明确记载;③西周时代“天下”观念就已十分清晰;④追求统一始终是政治观念中的基础,也是历史的基本倾向。 7、简述古代林木滥砍乱伐的重要原因及严重后果。答:林木乱砍乱伐的原因是统治者大兴土木。森林资源的损失,意味着黄河水土流失的加重。黄河中上游地区的森林被砍伐,牧场被开垦,严重破坏了自然植被。简述中国稻作农业未在岭南形成的原因.答:中国是稻作农业的故乡,然而稻作农业却起源于长江中下游,而不是原始籼稻资源更加丰富的岭南地区。为什么?专家指出,(1)这是因为岭南籼稻生长四季不缺,那里的原始居民没有改良籼稻品种的必要。倒是在长江中下游地区,籼稻的生长是有季节的,人们必须储备粮食才能过冬,在提高产量的要求下,籼稻才得以改良。(2)这说明,自然条件优越到“不劳而获”的地步,不利于文化的创造。当然,自然条件太恶劣也不利于文化的创造。(3)西方有史学家曾提出自然的“挑战”是人类文明产生的原因,看来不是没有道理的。中国古代文明国家最早在黄河中下游兴起,也就不难理解了。四、论述1、试述古代利用自然方面的成就。答:①土地的开垦:古代相当重视对土地的深度利用。先秦魏国“尽地利之教”;汉武帝时期推广“代田法”和“区田法”。②水利的兴修:既关系农业的兴衰,又关系环境的美恶。(2分)先秦两汉时期曾兴修郑国渠、白渠、六辅渠、龙首渠等水利工程。③运河的开凿:春秋战国至清朝后期的运河的开凿历史。2、试述构成区域文化的几个因素。答:区域文化构成的因素:①自然环境:人向提供物质的自然讨生计,这是自然文化决定地域人群文化的第一层次;越是人类生活的早起,该层次内容所起的作用就越大。②是地理条件的特殊或得天独厚。③是特定区域的人群,有明确的区域意识,并与其他人群形成竞争关系。④典型人物潜移默化的影响,也可以带出特定地域的文化特色。3、试论社区文化活动的意义。答:⑴社区文化活动可以跨越多民族的界限成为一个地方社会共同的活动。⑵社区文化活动可以保持各地方,各民族的文化特质。⑶社区文化活动可以保持地方文化遗产。1、简述新石器时代三大文明成就。答:①农业;②制陶;③石器的磨制与钻孔。2、简述多种族群向黄帝族聚拢的原因。答:①战争。据《史记》及相关文献记载皇帝与蚩尤曾经大战而皇帝获胜,有效实现聚族。②高级宗教确立。此前宗教混乱,“家为巫史”,而颛顼时代宗教祭祀行为专业化也起到了聚族作用。3、简述新石器文化的重要特征。答:①原始农业出现;②陶器的制造;③磨光石器的广泛使用; ④村落的出现及氏族的形成。4、简述中国文化基本规模形成的具体表现形式。答:①中国人形成了独具特色的生活理想。②中国人形成了特定的社会观念和思想法则。③先秦文化作用于后世文化。④稳定的价值观念对后代施以深刻影响。4、简述敬顺吴天的宗教现实功能。答:⑴其现实功能是“敬授民时”⑵其关系农业大事,是皇帝的后代建立宗教凝聚力的根源。⑶其得以聚族是因为该宗教中涵盖着先进的文化。因此,五帝时代的历史是文化带动着中华民族的最初凝聚。5、简述分封制的特点和意义。答:第一,作为一种制度,分封实际是承认了异族人的生存权利。 第二,旨在维护王室统治之分封,实 则形成了周王与诸侯共制天下的局 面。第三,分封制是一种激发历史创 造力的制度。1、试述魏晋南北朝时期 的民族大融合。答:南朝:中原人群 的南迁以及对南方的的开发过程也正 是南朝民族融合的过程。北方:十六 国时代许多北方政权的建立者,都深 受中原文化的熏陶。北魏与其说是汉 化,还不如说是南朝化。不能将北方 的民族融合简单的视为汉化,融合在 相当程度上也是胡化,隋唐立国思想 的很多方面,须要从其制定者的北方 文化背景去考虑,才能够得到准确的 理解。2、试述两汉经学的历史、文化 功能。答:⑴汉武帝的独尊儒术。汉 武帝接受董仲舒《天人三策》的建议, 罢黜百家,独尊儒术。是儒家思想正 是上升为国家统治思想,一直延续了 两千多年。⑵尊儒术,兴太平首先产 生影响的是文学方面,“诗三百”的影 响。两汉形成了诗词大国的风范。⑶ 经学与王莽新政。王莽新政就是受“尧 舜禅让”影响的结果。但其失败实则 是经学的失败,也是,只重视《周礼》, 而脱离现实的结果。3试述秦汉王朝政 治的新格局。答(1)郡县制的建立。 从秦朝建立到汉武帝初期百余年里, 王朝政治经历了郡县制与分封制的反 复。经过汉武帝一番切实的削弱政策 的实施,郡县制作为王朝惟一的政治 制度,最终得到确立。政治大一统的 格局由此正式形成。(2)中央集权制。 秦朝为中央集权制奠定了规模。最高 权力者称皇帝,表示他的地位与上天 同尊。皇帝之下是所谓的三公,即丞 相、太尉、御史大夫。(3)官员选拔 的文化标准。两汉选官方式多种多样, 最重要的有察举、征辟、考试等方法。 察举就是选举,是一种由下向上推选 官员人才的制度。三、1、简述造纸术 发明及传播的历史。答:①造纸术的 发明者相传为东汉时期的蔡伦;②蔡 伦用树皮、麻头、破布和旧渔网造纸; ③公元6世纪起,造纸术开始向东南 亚国家流传,公元8世纪传入中东阿 拉伯国家,公元12世纪传入欧洲。2、 简述自然范围内的服饰文化标志。答: ①环境标准,因自然环境的不同,服 饰略有差异;②性别差异,服饰体现 了性别的差异;③体形标志,人体高 矮瘦胖的不同,对服饰的要求也不同; ④年龄标志,不同年龄段的人们,服 装的颜色、样式等也有所不同。3、简 述家族共同体主要的文化功能①血缘 凝聚力。家族内部的每一个家庭按照 父系的血缘认祖归宗、单系传递。外 姓移入者为了求得同情和依靠,多与 原社会内部的大姓认干亲,寻求社会 关系网络的保护。②地缘凝聚力。家 族共同体的情感归属离不开特定地 域,共同的土地资源是他们分享生命 快乐的依据,是养育所有家庭的同一 条血脉。4、.简述我国古代行会的主要 管理方式。答:①祖师崇拜,各行各 业都有自己崇拜的祖师。②师徒传承, 手工行业的技术传承是在师傅和徒弟 之间进行的,徒弟入行、拜师、出师 都有一套行规,不可逾越。③行业禁 忌,传统手工业有许多行业忌讳,反 映了过去手工业生存艰难的另一面。 5、交通行旅文化主要由哪些部分组成? 答:⑴交通设备的习俗传承。⑵交通 工具的习俗传承。⑶交通行旅行业的 习俗传承。6、简述以工补农、以商求 富观念的文化价值。答:①它促成了 程式的出现;②它发展了市民文化; ③它打破了小农经济的视野,引进了 城市的信息;同时也把地方或民族文 化带到全国各地和世界其它地方。7、 农业岁时历法的文化价值。答:第一, 农业岁时历法即根据农耕生产而制定 的历法。第二,它是我国南北农业区 所共同发明,共同遵守的。第三,我 国官时和民时都受到他的影响。统治 阶级把它当做是礼制规范,向天下推 行。第四,农民按照二十四节气安排 农业生产生活,促进你了农业社会的 发展。四、1、论述居住建筑的文化含 义。答:居住方式:居住方式的选择 与自然条件有直接关系,居民住房主 要有五种形式:半穴式、井干式、干 栏式、石室、土木结构或木石结构。 居住建筑格局:多位前院后屋或前园 后屋的风格,既方便生活,也方便生 产。居室外格局:院墙、院门、庭院; 居室内格局:睡处、神位、照明、取 暖和贮藏、正房是最有中国特色的地 方。居住建筑仪式:选址仪式、上梁 仪式、贺新房仪式、使用家具仪式、 祭灶仪式、搬迁仪式。2、试述我国历 代农书提出的主要农业经营思想与生 产知识。答:①统筹水土利用规划, 提整地出、浇水、种植、施肥、收获 和准备在耕一盘棋的思想。之处关键 在于控制人对自然资源的使用限度。 任何农业经营都不得违反自然规律。 ②调整好农业生产关系,要整体的看 待农作物的栽培,要协调好劳力、农 具与社会组织之间的关系,注意选择 雇工,勤俭持家等。③“荒政”思想。 认为全社会都要有居安思危的自觉意 识,在中央国策中应该包括“备荒”” 救荒”的内容。④人力胜天说。即调 整人的知识能力和奋斗精神,认为人 的合理作为可以弥补自然资源的不 足。取得人力胜天的成绩。3、试析中 国古代建筑的人文性。答:中国古代 建筑具有强烈的人文性。在建筑中寄 寓着浓厚的思想观念。这是中国古代 建筑的一大特点。在这些人文思观念 中,最突出的是讲究秩序,突出等级, 受儒家伦理思想的影响。中国古代建 筑具有“主次分明,秩序井然”的位 序观。在同一个建筑组合中建筑物之 间的排列有着明确的正偏,内外之别。 这种区别象征着使用者的地位尊卑, 故宫即是如此。中国古代建筑中的等 级观念,除了体现在布局方面之外还 体现在建筑的规模和室内外的装修, 装修方面。4、试述中医药学的腹脏、 经脉、针灸等学说与民族文化的关系。 答:中医药学的腹脏、经脉、针灸等 学说与民族文化的关系有:一、腑脏 学说1、这一学说的核心是“脏象之 说”,即认为五脏六腑长在体内,但其 形象和功能却表现于外。腑脏在中医 学里,不是一个单纯的生理解剖概念, 更重要的是一个传统文化概念。它的 思想来源,是阴阳五行学说。2、在这 一体系中,把五行观念与人体器官相 配属,分列为五官、五色、五味、五 音和七情,然后将它们的内性外象联 系在一起考察,通过观察人体外部器 官与内脏之间的某种联系和根据临床 经验进行辨证施治。它在祖国医学几 千年的实践中取得了实证效果。二、 经脉学说1、经脉学说惟见于中国的传 统医学理论,而不见于世界其他国家 的古代医学。它是中医基础理论的另 一支柱。这一学说把人的生理系统看 做是一个如环无端的循环圈,其中有 人体器官的配属关系,人体与外界的 天人配合关系,人体中的气结、聚、 散与筋肉的关系等,并将其付诸临床 应用。2、这一学说对于中医学的长期 临床实践,确实起到了重要的指导作 用。它强调人体的外表、肌肉与内脏 的密不可分的联系,强调生理健康与 心理健康的辩证关系,并以此为依据, 进行诊断和治疗,这与中国传统文化 的整体观念和事物联系发展的观念是 相一致的。三、针灸学说针灸是针刺 与灸法的合称,它的出现是对经脉学 说直接应用的结果。1、按照针灸学说, 只要确定了某种病症属于某一经脉, 即可直接施治,其要点是辩证解决人 体健康中的“阻滞”与“疏通”的矛 盾关系。这既是一种治疗方法,也是 中国传统文化的一种思维方法。2、许 多人认为,中国传统医学可以分为两 大体系,即以神农——草药为脉络的 药物学治疗体系,和以黄帝、伏羲— —针砭为脉络的针灸学治疗体系,便 是从医学史和文化史两方面加以综合 得出的。针灸学说是中国传统医学文 化的一种创造,现已广泛流传于世界 各地。1、秦汉以后,中央集权的君主 专制制度有哪些特点啊?答:①皇帝 总揽天下大权;②拥有庞大的官僚办 事机构;③严密的人身控制。2、.简述 科举制的历史地位。答:①在科举制 度下,古代中国建立起稳定的文官制 度,这种文官考试制度在人类制度史 上有着重要的开创意义。②它在世界 文明史上产生了广泛影响,现代西方 实行的文官制度,就是以中国古代科 举制度为基础。3、中国传统礼俗规约 的特点是?答:⑴传统礼俗的等差性。 ⑵传统礼俗的调和性。⑶传统礼俗的 规范性。4、简述中国古代法律制度的 文化特色。答:①以儒家伦理学说作 为立法的指导思想;②家族本位的伦 理法占有重要地位;③皇权至上,法 自君出;④强调等级特权,主张同罪 异罚。5、简述我国宗法制度的特点。 答:宗法制的特点在于,一方面利用 自然血缘关系确定人们的社会关系, 另一方面,又运用自然血缘关系将人 们紧紧地联系在一起。从而限制人们 社会关系的发展。简述“家天下”的政 权模式。答:宗法制度原则的本质就 是家族制度的政治化。王朝的更迭往 往是新旧家族的代兴与衰亡。(1)秦 始皇以郡县制取代分封制,对宗法血 缘关系进行强力破坏,但是他并没有 摆脱宗法关系的控制,他自命为“始 皇帝”,希望其家族子孙世代传袭皇 位。(2)(《史记·秦始皇本纪》)秦二 世灭亡之后,代之而起的是刘姓的汉 家天下,布衣刘邦一旦成为帝王,就 将天下视为私产,他与臣僚约定,“非 刘氏而王,天下共击之”。(3)在皇位 继承上,历代帝王大多遵循嫡长子继 承制的宗法原则。历史上虽然不乏非 嫡传子孙继承皇位的事例,但他们没 有越出血亲的宗法范围,他们只是对 嫡长子继承制的补充。(4)齐家治国 平天下是传统社会的政治理想,齐家 与治国并称,人们能够将齐家术转换 为治国策,说明家国一体的互通性质。 四、1、论君主专制制度对中国传统社 会的影响。答:①秦汉时期确立中央 集权的君主专制制度,在中国传袭达 两千年之久,成为影响中国历史进程 的重要的政治文化传统。②秦汉以来, 皇帝总揽天下大权,拥有庞大的官僚 办事机构,严密的人身控制,成为中 国传统社会政治文化的显著特点。③ 秦汉以后,君主专制制度日益成熟与 完善,高度集中的专制王权,给传统 中国社会打下了深刻的烙印。在专制 社会里,中国古代社会文化形态与民 众生活几乎很少不收到集权政治的影 响,特别是高度专制的明清时代,无 孔不入的政治权利造成了传统文化的 沉闷与单调。2、试述中国古代家训族 规的礼俗教育与规范功能。答:①以 孝悌之道为礼俗之本,强化家族内部 的伦理关系;②以诚信忠厚为修身之 本,塑造传统社会的理想人格;③以 规劝惩罚的礼俗规条。3、试述中国古 代法律制度的文化特色。答:其文化 特色主要表现在以下方面:第一,以 儒家理论学说作为立法的指导思想。 第二,家族本位的伦理法占有重要地 位。第三,皇权至上,法自君出。第 四,强调等级特权,主张同罪异罚。4、 试述科举制在历史上的地位与作用 答:地位:在科举制度之下,古代中 国建立起稳定的文官体制,这种文官 考试制度在人类制度史上有开创性的 意义。它在世界文明史上产生了广泛 影响,现在西方文官制度就是以中国 古代文官制度为蓝本。作用:⑴科举 制度将儒家思想全面推广到社会的各 个层面,成为国家的精神内核。⑵科 举制强化了读书尚文的文化传统,造 就了大批的文化人才。5、试述中国古 代法律制度的文化特色答:其文化特 色主要表现在以下方面:⑴以儒家的 伦理学说作为指导思想,⑵家族本为 的伦理法占有重要的地位。⑶皇权至 上,法自君出。⑷强调等级特权,同 罪异罚。三、1、简述中国古代整体思 维的特征。答:重整体;②重体悟; ③以经验为基础;④直观思维。2、简 述中国古代类比思维的特征。答:① 中国古代类比思维是就“天、地、人、 万物”之间的外部特征与内在属性进 行类比。②中国古代类比思想中,有 一种叫做“观物比德”,是人与物的类 比,是说用物的外部特征和内在属性 来类比人的品德、志行。3、简述五帝 至商的宗教崇拜分野。答:该历史时 期的宗教崇拜大体为:①超自然神; ②天神地衹;③祖先神:④商朝力量 愈大,祖先神灵祭祀愈占主要地位。4、 简述宋明理学的宗教功能。答:①宋 明理学将隋唐佛教的心性理论融入自 己的义理之学中,表明这种义理学的 实质是儒学化的佛性理论,因而带着 明显的宗教功能。②理学家们强调与 实行“半日读书,半日坐禅”,“主静, 居敬”,“戒惧、慎独”,也是有宗教意 识、功能的。6、简述中华民 族的理想人格。答:中华民族的理想 人格,主要以儒家的理想人格为代表。 儒家所崇尚的理想人格是圣贤。圣贤 包括两个理想两个理想人格的追求, 即圣和贤。圣指圣王,贤通常用“君 子”一词表示。7、简述古代关于天人 关系的几种观点。答:⑴“天人合一” 起源于西周,这是天人关系的一种全 面的观点。⑵“天人交胜“由唐代的 刘禹锡提出。⑶”天人之分“由战国 荀子在《天论》中提出。8、简述中国 古代原始宗教的种类。答:早在远古 时代我国就出现过自然神崇拜、动物 崇拜、鬼魂崇拜、上帝崇拜、祖先崇 拜等原始的宗教形式。而在中国古代 的原始宗教中,对后来的社会影响较 大的有上帝崇拜,祖先崇拜,鬼魂崇 拜,前兆迷信和占卜等。9、简述“天 人合一”的含义。答:“天人合一”是 中国传统哲学的一个独特的观点,主 要包含两层含义,一是人是天地生成 的,人的生活服从自然界的普遍规律。 二是,自然界的普遍规律和人类的道 德的主要原则是一而二,二而一的。 10、简述中国画的主要特点。答:(1) 追求神似,注重意境。中国画不要求 形象逼真,而强调传神达意。(2)以 墨线为造型的主要手段。(3)与诗、 书、印密切配合。四、论试题1、答: 人生礼俗指依照人生历程的阶段性变 化而定期进行的礼仪习俗,它主要包 括诞生礼、成年礼、婚礼和丧礼,其 家族性特征在每一阶段均突出地表现 出来。从诞生礼仪看,婴儿一出生, 甚至在出生之前就收到父族与母族的 精心呵护,婴儿的教育和培养成为家 族的重要事务;成人礼原本是独立的 人生礼仪,由于传统的社会重视家庭 形式,个人只是家庭的一个成员,个 人的资格与能力从属于家庭的需要, 因而成年礼逐渐演变为婚礼的一部 分;婚姻礼仪的各个缓解都要贯穿着 明确的家族原则,婚姻缔结着家族关 系,婚姻延续了家族的香火;而丧葬 礼仪中最能体现家族社会关系的是丧 服礼制,亲属要依与死者血缘关系的 远近穿着不同的孝服“守制”。2、论 中国古代“知行合一”说的主要内容 及基本特点。答:①中国古代“知行 合一”说的主要内容是道德修养、道 德实践。②中国古代“知行合一”说 的基本特点是并不注重重建构理论体 系,而强调身体力行,以便真切地认 识并实践“天道”和“人道”。3、试 述《礼记?大学》所提出的古代教育 的三大目标和八个步骤。答:中国古 代教育的总体目标集中反映在《礼 记.大学》关于大学之道的论述中。《大 学》一开篇就明确提出了当时大学教 育的三大纲领:“大学之道在明明德, 在亲民,在止于至善。”这实际上也就 是中国古代教育的三大目标。大学教 育的首要目标是使人“明德”,第二是 “亲民”,“泛爱众而亲仁,第三是达 到道德修养的最高境界,即“止于至 善”,这是儒家对教育所提出的最高目 标。为了实现这三个目标,《大学》还 提出了教育的八个步骤,即格物、致 知、诚意、正心、修身、齐家、治国、 平天下。《大学》提出的大学教育目标 一直是中国古代教育所遵循的原则, 对中国古代教育的发展发挥了重大作 用。4、试述“天人合一”观念对中国 文化的影响。答:在中国哲学中,天 人合一的观念占有主导的地位,给予 中国文化及其发展以长远而广泛的影 响。择其主要而言之,这种影响有三 个方面:①造成了中国文化中整体系 统的、辩证发展的思维方式;②造成 了追求和谐社会的理想主义倾向;③ 造成了“诚明合能”的人生修养哲学, 推动人们在成己成物、人我交融中实 现人格、品德的完善。“天人合一”的 哲学观念也给中国文化及其发展以负 面的影响,思维方式过分强调整体联 系与统一,缺乏必要的分析和论证。 过分强调社会和谐与统一;缺乏进取 精神,空想的理想主义使主观脱离实 际;重体验不重客观观察,限制了实 证科学的发展。5、试述商代文化的宗 教特征。⑴甲骨文和青铜器的发掘出 土,堪称20世纪考古学最伟大的发现, 而这些发现,殷商宗教生活有关。事 例:殷人生活几乎无事不占卜,巫师 在商朝政治生活中占有崇高地位等。) ⑵自五帝时期以来,宗教崇拜大体有 超自然神,天地神祗和祖先神三大分 野,好鬼神的殷商人自然会全盘继承。 事例:殷人一年中总是不间断的祭祀 祖先神。三、1、简述中国人语言观念 的内容。答:①是对语言这一文化事 象的看法,如对语言的崇拜、对语言 与社会关系的讨论等;②是对语言交 际能力的不断追求,如对规范语言的 追求,对言辞技巧的不断探索等。2、 谚文:古代朝鲜仿照汉字创制的文字, 字母近似汉字的笔画,每个音节拼成 一个方块。3、简述建国后在语言文字 规范方面所开展的工作。答:建国以 后,党和政府亲自领导了文字规范工 作。一是针对方言歧义不变交流的情 况,大力推行普通话;二是针对汉字的 繁难的问题,对文字进行简化运动, 并不断针对语言文字中的新问题进行 及时的规范工作。4、简述科举取士制 度对我国语言文字的负面影响。答: 中国科举取士制度,带来语言教学中 重文轻口语的做法,和作文中言文脱 节的严重后果。言文脱节不利于文化 的普及,却利于文化的统治和专治。5、 简述中国人的汉字观念。答:对汉字 的认识是与中华民族的盛衰紧密联系 在一起的。从古至今的汉字观念主要 有:汉字崇拜;汉字否定;对汉字的 多维思考。6、传统语文教育包括哪几 项主要内容?答:传统的汉字教学包括 汉字教学和识字教学。传统的语言教 学包括句子训练和作文训练。7、简述 孔子“正名”思想的历史影响。答: 孔子由语言的社会功用而提出的“正 名”问题,使中国对“名”“实”的思 考,并没有像西方人关于词与物的讨 论那样带有浓厚的思辨色彩,而是始 终关注语言的政治伦理作用和社会实 践作用。8、简述汉语在世界语言中的 地位。答:与世界上的其他语言类型 相比,汉语具有自己的特点。(1)按 词的构造特点来看,汉语的词用在句 子里时,没有表示语法关系的词形变 化。按句法结构的表达方式来看,汉 语不通过词的形态变化表示语法关 系,而是借助于虚词和词序来表示词 与词的语法关系。(2)汉语是有声调 的语言,古代汉语有“平、上、去、 入”四声,现代汉语普通话有“阴平、 阳平、上声、去声”四个声调。声调 是汉语构词的一种手段。(3)从音义 对应的角度来看,汉语的特点是一个 音节对应于多个词(语素)。因为多词 同音,所以单凭语音会发生理解的歧 义,在某些特殊的情况下,单凭听到 的语音无法领会语义。9、新中国建立 后,为促进民族语文工作顺利进行采 取了哪些措施?答:新中国建立后,政 府制定了一系列法规政策以保障各少 数民族使用和发展自己的语言文字的 合法权利,并采取了许多切实可行的 措施保证民族语文工作的顺利进行, 比如:(1)开展大规模的少数民族语 言调查,并为一些少数民族创制、改 革文字;(2)不断扩大民族自治机关 使用民族语言文字的自治权;(3)在 民族地区的学校,凡有本民族通用语 言文字的地方,大都实行双语教学; (4)在中央和各民族地区,广泛建立 民族文字的出版、翻译机构,建立民 族语言广播电台、电视台;(5)大力 培养少数民族语文人才。这些尊重和 发展少数民族语言文字的政策和措施 对于坚持民族平等、团结和促进各民 族的共同繁荣具有重要意义,也仍是 今后民族语文工作的方向。四、1、试 述汉语、汉字对中华文化的贡献。答: ①汉语使用地区的扩大和共同语的存 在,在汉民族共同思想、文化的形成 中扮演了重要角色,也为各民族的相 互交流融合和统一的中华民族的形成 起到了非常重要的作用。②汉字表意 文字的特点,使不同方言区的人能够 顺利交流,对中华文化的统一和中华 民族的凝聚力的形成都起了至关重要 的作用。三、1、简述禅宗的传播。答: 禅宗相传为南朝宋末菩提达摩在河南 少林寺创立,后分北、南两宗。后来 南宗成为禅宗正宗。中晚唐时期禅宗 开始流传城外。2、简述中华民族传统 美德的作用。答:这些美德不仅为过 去中华民族的发展提供了巨大的力 量;也会为未来中华民族的腾飞发挥 重要的作用。3、简述建设有中国特色 社会主义的文化纲领。答:以马克思 主义为指导,以培养有理想、有道德、 有文化、有纪律的公民为目标,发展 面向现代化、面向世界、面向未来的 民族的科学的大众的社会主义文化。 4、简述明清之际的耶稣会士在沟通中 西文化方面所起的作用。答:①向中 国广泛传播西方科技、文化,包括西 方的自然科学、古典哲学、史地、音 乐、美术等。②向西方介绍中国文化。 5、简述近代中国文化变革的历程。答: 从物质层面的文化变革,进入制度层 面的文化变革,最后进入文化变革的 核心——价值观念层面的变革。四、1、 试述中国文化现代化的道路。答:① 中国文化的现代化只能走“古今中外, 综合创新”的道路。②“古为今用, 洋为中用,批判继承,综合创新”,这 一文化主张是先进的中国人经过长期 探索和缜密思考的结果。③一部中国 近代史,尤其是20世纪以来中国现代 化的实践,已经雄辩证明,综合创新 之路,是中国文化的现代复兴之路。 1

全国2019年04月自考(00321)中国文化概论试题及答案

C029·00321(通卡) 绝密★启用前 2019年4月高等教育自学考试全国统一命题考试 中国文化概论 (课程代码00321) 注意事项: 1.本试卷分为两部分,第一部分为选择题,第二部分为非选择题。 2.应考者必须按试题顺序在答题卡(纸)指定位置上作答,答在试卷上无效。 3.涂写部分、画图部分必须使用2B铅笔,书写部分必须使用黑色字迹签字笔。 第一部分选择题 一、单项选择题:本大题共30小题,每小题1分,共30分。在每小题列出的备选项中只有一项是最符合题目要求的,请将其选出。 1.文化交流是一个 A.双向互动的过程 B.不平等的过程 C.反向逆动的过 D.单向反动的过程 2.司马迁:送宇宜,次民好稼稿,殖五谷,有先王之遗风”。说的是 A.山西地区 B.河东地区 C.关中地区 D.江南地区 3.在血缘家庭中,进行权力传递和财产继承的中心是 A.嫡庶 B.血统 C.男性 D.女性 4.明代大医学家李时珍的伟大著作是 A.《黄帝内经》 B.《本草纲目》 C.《千念药方》 D.(神农百草经》

5.惟见于中国的传统医学理论是 A.腑脏学说 B.针灸学说 C.经脉学说 D.本草学说 6.造纸术的发明者传说是东汉时期的 A.毕异 B.韩信 C.蒙恬 D.蔡伦 7.从夏朝初期一直到周人建国之前,历史的显著特征是 A.族群的代兴 B.家庭的代兴 C.诸候国的代兴 D.部格的代兴 8.早期法家的代表人物之一是 A.韩非子 B.惠施 C.管仲 D.公孙龙 9.人类存在和文化创造的先决条件是 A.气象环境 B.地理环境 C.社会环境 D.人文环境 10.隋唐以后,中央机构三省六部制中的六部求属于 A.尚书省 B.中书省 C.门下省 D.元外省 11.中国地势的主要特征是 A.东高西低 B.中高东低 C.西高东低 D.北高东低 12.《史记》记载,周武王伐纣时,“不期面会”的诸候有 A.二百诸候 B.三百诸候 C.五百诸候 D.八百诸候 13.宋代文学的代表样式是 A.赋 B.诗 C.词 D.戏剧 14.夏朝开始了族群相处的一种新的关系模式,那就是 A.和睦相处 B.战争征服

自考中国文化概论复习资料

如对您有帮助,请购买打赏,谢谢您! 绪论 一、知识题 1、中国文化又称中华文化、华夏文化、炎黄文化。 2、中国文化分为四种:生产生活文化、制度文化、思想观念与精神文化、语言文字文化。 二、名词解释: 1、文化产品广义的文化产品指人类创造的一切提供给社会的可见成品,既包括物质产品,也包括精神产品。狭义的文化产品专指精神产品,纯粹实用的生产工具、生活器具、能源资材等,一般不称为文化产品。 2、文化内涵;把一些不属于狭义文化的事物中所具有的人文特性,称为事物的文化内涵。 3、文化现象:指人类文化发展过程中呈现妯的某种外部状态和联系。文化现象包括文化事象。 4、文化事象:当一种现象以同样的形式反复出现时,其中就含有规律性,成为某一历史时期、某一国家文化发展中带有典型和标志作用的事情,这些现象称为文化事象。 5、文化观念:一个时期某一阶层或某一行业的人群对文化问题所持的态度和看法,或在某一文化事象里所表现的意识形态,诸如价值观、审美观等等,称作文化观念。 6、文化思潮:某种文化观念及与之相关的文化事象,在某一特定时期,在一定的背景下,对社会产生广泛影响,为多数人所赞同和奉行,形成一种潮流,称作文化思潮。 7、文化政策:指一定时代、一定的社会条件下,行政机构对文化领域的问题所颁布的相关规定和对策原则。 8、两个文化层面:指上层文化与底层文化。上层文化是宫廷文化与上层文人所创造、拥有的文化。底层文化指民间文化,即不依赖于统治阶级的广大人民及其精英人物所创造、拥有的文化。 三、问答题 1、“文化”名称的来源? 答:A“文”的本义是“错画”,也就是花纹。在人类认知领域里,“文”引申为后天形成的品德、修养,与表示先天素质的“质”相对。“文”在政治领域里,引申为文治教化,文治也就是礼治,与“武功”相对。B“化”的本义是改易。包括宇宙生成以后的“演化”和“分化”。 2、文化的古代意义、现代意义? 答:1)中国经典的“文化”是指人的后天修养与精神、物质的创造。修养属改造主观世界的范畴,创造属改造客观世界的范畴。2)基于汉语“文化”概念的传统解释,学术界经常把它与英语的culture对译。culture的原义是指人类所创造的物质文明,由于物质创造包含人的智慧,与精神文明难以截然划分开。 3、广义文化与狭义文化的定义? 答:1)广义的文化是人类在长期的历史发展中共同创造并赖以生存的物质与精神存在的总和。应把握三要点:A广义文化是与人类及人类的创造活动相联系的,是以人为中心的概念;B广义文化是一个历史概念,它涵盖人类历史的全过程,是一个传承发展的综合概念;C广义文化的外延涵盖物质创造和精神创造的全部。2)狭义的文化又称人文文化,是某一社会集体在长期历史发展中经传承累积而自然凝聚的共有的人 文精神及其物质体现总体体系。应把握三要点:A狭义文化不但以人为中心,而且以人的精神活动为中心,即使观察物化世界,也以其中的人文精神为内核;B狭义文化关注的不是个别人的精神活动,而是经历史传承累积凝聚的共有的、成体系的人文精神;C狭义文化关注的不仅是全人类的普遍共性,而且更注重不同民族、阶层、集团人文精神的特点。所以狭义文化的定义不但适用于人类文化学,且适用于民族文化学、国别文化学等较为具体的范围。 4、民族文化和国别文化及其特点? 答:1)不同的民族有自己不同于其他民族的文化,文化的差异与特色是划分民族的标志之一。反之,在社会学领域里,民族也是文化划分的依据。以民族特点为标志的文化就是民族文化。其特点是每一个民族的文化都不会因此而丧失其鲜明的民族特色、地域特色。2)中国文化又称中华文化、华夏文化、炎黄文化,它属于国别文化。国别文化是以国家为划分文化的社会依据,多民族国家的文化即在统一的国家内民族共同体的文化。国别文化以某一国家特有的历史与国情为基础。其特点是中华文化具有多维性特点,是由中国境内56个民族构成的共同体文化。 5、传统文化和对传统文化的错误认识 答:1)中国传统文化,指的是以中华文化为源头、中国境内各民族共同创造的、长期历史发展所积淀的文化。2)错误认识:有人把传统文化等同于古代文化,从而认为讲究传统即是复古,甚至认为传统与现代化是不能并存的,或认为要实现现代化必须反传统。这种认识恰恰忽略了现代化进程仍然是传统文化发展的一个部分,一旦否定了传统,现代化与民族特点也就是中国特色就要脱节,与我们追求的目标是不一致的,也有人认为发扬传统就要拒绝引进和借鉴,或认为中国传统与西方文化是截然对立的。这种认识也是片面的。任何一种民族传统,在各个历史时期,都要受到其他民族文化的影响,引进和吸收其他文化一旦成为现实,就是说,这些被吸收的外来文化一旦与自身的文化相融合,它便也成为传统文化的一部分。 6、文化传统及其性质? 答:每一个民族、每一个国家的文化,既因时因地而异,又有一定的稳固性和延续性,文化传统是贯穿于民族和国家各个历史阶段的各类文化的核心精神。这种核心精神,也是上层文化和底层文化所共有的,尽管彼此的表现形式不完全一致。其性质是文化传统具有一定的稳定性和延续性,传统不是一成不变的。 7、有关中国文化分科的知识? 答:关于文化的分科,有两分法(物质文化和精神文化)、三分法(物质、制度、精神)、四分法(物质、制度、风俗、思想价值取向或物质、制度、精神、语言)。以及更多的分类法(例如,有物质、社会关系、精神、艺术、语言、风俗六分法等等)本课程采用四分法:生产生活文化、制度文化、思想观念与精神文化、语言文字文化。 8《中国文化概论》课程与中国文化史的区别? 答:中国文化史是以中国文化历时演变为主要内容的。而中国文化概论虽然也有一定的篇幅来梳理中国文化的发展脉络,但其目的是为了使学习者对中国文化的发展具有一个总体的认识,从而树立传统文化的历史观念。 第一章、中国文化的地理背景 一、知识题 1、灾荒主要指旱、涝、蝗、风、雹等 2、司马迁把当时的天下划分为四大基本经济区:山西地区、山东地区、龙门—碣石以北农牧交错地带、江南地区。中国自然区域的现代地理学划分:东部季风区、西北干旱区、青藏高寒区。 3、在保护自然方面,古代有一重要观点,就是孟子提出的不违天时观念。 4、在保护西北地区环境方面起作用最大的,还是南北朝至唐朝中期牧马场地的广布。 5、古代改造利用自然的另一项重要举措是开凿运河。春秋战国时期,楚国、吴国、齐国、魏国都有运河的修建,如邗沟、鸿沟等;吴国的运河已经与黄河、济水相接。秦汉至南北朝,也多有运河的开凿。秦汉时有连接湘江、漓江的灵渠,加强长江漕运的漕渠、阳渠,纵贯河北平原的白沟、平虏渠、泉州渠、新河、利漕渠等等,还改造了先秦旧有的各种水运沟渠。魏晋南北朝连接江、淮、河、海的运河网已经形成。另外还疏凿了广济河、金水河、惠民河,与汴水共称通漕四渠。又有京杭大运河的开通,北起通州,南达杭州。 6、古代开发利用自然方面的主要失误,是土地的过当开垦及林木资源的过量开采。林木的滥砍滥伐,在北方造成的灾难性后果更加严重。长江、黄河以及淮河越来越大的危害,都与片面的重农思想有关。 二名词解释 1、三个大自然区:用现代地理学的观点观察中国地理的自然特征,可以将广大的中国领土划分为东部季风区、西北干旱地区和青藏高寒区。 2、古代的九州:即冀、兖、青、徐、扬、荆、豫、梁、雍九州。冀州(西河以东,东河以西)、兖州(古济水、黄河之间)、青州(渤海、泰山之间)、徐州(黄海、泰山、淮河之间)、扬州(淮河以南、大海以西)、荆州(荆山以南、衡山以北)、豫州(荆山以北、黄河以南)、梁州(华山以南、怒江以东的汉中、四川盆地)、雍州(西河以西、黑水以东)。[《尚书》之《禹贡》篇] 3、方志时期:因为明清两代我国多数地方都有了方志,对区域性的气候做了更为详细的记录,特别是对认识各种异常气候所引起的灾害很有帮助。所以,竺可桢把从公元1400到1900年的第三个大的气候时期称为“方志时期”。方志时期又称寒冷时期。 4、仪器观测期:因为自1900年以后直到现在,有了测量温度及气象观测的仪器,所以,竺可桢把此一时期称为“仪器观测期”。 5、地缘:此地缘概念不同于现代的领土观念。它指的是当中原文化中心形成后,与北方范围更加广阔的草原游牧文化之间的关系。 6、通漕四渠:指的是以宋都汴京为中心开凿的四条用于漕运的人工运河,即汴河(或称通济渠)、广济河、金水河、惠民河。 三、问答题 1、关中及晋北地区的地位及对中国文化的影响:关中及晋北地区的地理位置在中国显得十分重要。关中地区是四塞之地,黄河在它的西、北、东三面环绕,南面是秦岭山脉,西北有六盘山、贺兰山,北有阴山山脉、东有吕梁山脉及潼关之固,此地还有泾水、渭水流过,真可谓沃野千里,山河表里。而且此地有富裕的经济后方,有方便的交通,进可攻退可守,所以成为中华文化重要的发祥地之一。周、秦、汉、唐等王朝都在这里建都,创造了灿烂的中国文化。晋北地区坐落在山西高原上,也是中国文化重要的发祥地,据说尧舜时期就在谷地的偏南地区建立过都城。而晋北地区又与蒙古高原相连接,是内迁的北方民族进入中原地区的要路,再加上太行山脉的某些断裂处又可以直通华北地区,所以历来就有山西居“天下形势”之说。总之,正因为关中及晋北地区所处的地理位置的重要,不仅使大量的人群聚集在这里,而且又使便利的交通让各地域之间进行相互的文化交流,因此对中国文化的发展产生了重大的影响。 2、中国地形地势特点? 答:中国处于世界最大的欧亚大陆东部,东临浩瀚的太平洋。在中国境内地势西高东低,地形呈阶梯状分布:第一个阶梯是西部的青藏高原,平均海拔在4000米以上,是我国大江大河的发源地。第二个阶梯是青藏高原往东往北,海拔都在2000米至1000米以下,这里分布着云贵高原、蒙古高原、黄土高原及四川盆地、汾河谷地等。第三个阶梯则是北起大兴安岭、中经太行山、南至巫山一线以东及云贵高原东缘以东的中国东部地区,其平均海拔低于500米,滨海地带更低于50米。 3、中国地理的整体性特征? 答:作为欧亚大陆的一部分,中国地理面积差不多与整个欧洲一样大。

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