组织结构和企业文化外文文献翻译中英文2019-2020

外文文献翻译原文及译文标题：组织结构和企业文化外文翻译中英文2019-2020文献出处：Jonathan Newton, Andrew Wait, Simon D. Angus. Games and Economic Behavior, Volume 118, November 2019, Pages 354-365译文字数：4000多字英文Watercooler chat, organizational structure and corporate cultureJonathan Newton, Andrew Wait, Simon AngusAbstractModeling firms as networks of employees, occasional collaborative decision making around the office watercooler changes long run employee behavior (corporate culture). The culture that emerges in a given team of employees depends on team size and on how the team is connected to the wider firm. The implications of the model for organizational structure are explored and related to trends in the design of hierarchies.Keywords: Collaboration, Teams, Hierarchies, Delayering, Networks, EvolutionApple is a very disciplined company, and we have great processes. But thats not what its about. Process makes you more efficient. But innovation comes from people meeting up in the hallways or calling each other at 10.30 at night with a new idea.Steve Jobs, founder of Apple Inc.IntroductionPeople talk, share ideas, and collaborate when it is mutually advantageous to do so. Workers bring their collaborative nature with them to the workplace and to their dealings with their colleagues, with whom they interact on shopfloors, in meetings, on production lines and during coffee and lunch breaks. In this paper we consider collaborative decision making in the social environment of the workplace and, using a simple model of adaptive decision making, show that this can have dramatic and far reaching effects on corporate culture and the optimal internal structure of organizations.Our model takes the well documented fact that humans are particularly good at mutually beneficial collaboration (Tomasello, 2014), and incorporates this fact into a noisy variant (Young, 1998) of the best response dynamic that has been the bread and butter of economic modeling sinceCournot (1838). We model firms as networks of employees, each of whom can choose a safe action or a risky action. The risky action represents innovative, even speculative, behavior within the firm. An employee will only find it in his interest to take the risky action if enough of his neighbors in the network do likewise. Within firms, employees are divided into teams. A team is a group of employees who interact together, although they may also interact with others outside of the team. The team represents an employees work group, department, or even a corporate board or senior management committee.The ability of employees to engage in collaborative action choice is modeled by the idea of a watercooler, around which small groups of employees within a team can chat and form collaborative intentions. If there are no watercoolers, so that employees cannot share intentions, the model reduces to the canonical model ofYoung, for which the action profile in which every player chooses the safe action is always a long run equilibrium (Peski, 2010). This result no longer holds when small groups of players can occasionally meet at the watercooler to form shared intentions, coordinating their action choice to their mutual benefit. Instead, by incorporating this basic facet of human nature into the model, we obtain a diversity of behavior, dependent on network topology.We find that in order for members of a given team to play the risky action in long run equilibrium, some conditions must be satisfied. (i) Firstly, the team must not be too large. The larger a team is, the less likely that a fixed amount of collaborative decision making around the watercooler will have an impact on long run behavior. (ii) Secondly, sufficient numbers of employees must be able to coordinate their strategic choice at the watercooler; that is, communication within the team must be strong enough to generate enough collaboration to overcome the systemic bias in favor of the safe action. (iii) Thirdly, the team must not be so small that the influence of its members external connections can cause them to play the safe action, or, if the team is indeed that small, then all members connections outside of the team must be to teams that play the risky action. In other words, the external influence from those outside of the team who play it safe must be limited. These conditions provide guidance for organizational design: they can be used to promote or prevent different behaviors in different parts of an organization. Section5provides examples related to delayering and job rotation.Each of these conditions helps to explain empirical facts. Condition (i) provides an explanation for why companies seeking to promote innovation create organizational structures based around small teams (Cook, 2012;Stross, 1996). Condition (ii) helps explain the efforts that firms take to increase spontaneous interaction and facilitate informal communication between workers; that is, to create larger watercoolers (Evans, 2015). Condition (iii) helps explain why organizations seek to foster independence within teams and even isolate research units from other parts of the organization (Sloan, 1964).Related literatureThis paper contributes to several strands of literature. The practical contribution is to the literature on the importance of the workplace social environment the nature and patterns of interaction between workers in a firm (see, for exampleBandiera et al., 2005;Gibbons and Henderson, 2013;Kandel and Lazear, 1992). We demonstrate how the facilitation of collective agency by the workplace social environment can have a significant effect on corporate culture. LikeKreps (1990)andHermalin (2001), we model corporate culture as an equilibrium outcome played in a coordination game. To do this we turn to the literature on adaptive decision making and evolution, which allows us to develop a simple explanation of some aspects of corporate culture, providing an alternative, even complementary, theory to the shared beliefs model ofVan Den Steen (2010). Evolutionary models often focus on long run equilibria. This is similar to how the relational-contracting literature adapts long run folk theorems to study firms (Baker et al., 1999;Levin, 2003;Li et al., 2017), the difference being that evolutionary models impose very low rationality requirements on agents. Such low rationality models have had success at explaining laboratory data (Chong et al., 2006) as well as empirical phenomena as diverse as crop-sharing norms (Young and Burke, 2001) and the wearing of the Islamic veil (Carvalho, 2013). The current paper shows how the incorporation of collective agency into such models can lead to even richer empirical predictions whilst retaining the simplicity and elegance of evolutionary methodology.The incorporation of collective agency into perturbed evolutionary dynamics is a relatively new and rapidly growing literature (Newton, 2012a,Newton, 2012b;Newton and Angus, 2015;Sawa, 2014;Serrano and Volij, 2008), although considerable work has been done in the context of matching, where pairwise deviations represent intentional behavior by coalitions of size two (Jackson and Watts, 2002;Klaus et al., 2010;Klaus and Newton, 2016;Nax and Pradelski, 2014;Newton and Sawa, 2015). The proclivity of humans to engage in collective agency is well documentedand recent research in developmental psychology has shown that the urge to collaborate is a primal one, manifesting itself from ages as young as 14 months (Tomasello, 2014;Tomasello et al., 2005;Tomasello and Rakoczy, 2003). Recent theoretical work has shown that the ability to act as a plural agent will evolve in a wide variety of situations (Angus and Newton, 2015;Newton, 2017;Rusch, 2019). The authors of the current paper believe that the evidence in favor of the incorporation of collective agency into models of human behavior is overwhelming. Furthermore, adaptive/evolutionary frameworks are ideal for this as, in contrast to static analyses, they explicitly model behavior both in and out of equilibrium.Finally, we note that work on collective agency in evolutionary dynamics builds on a broader literature on coalitional behavior in game-theoretic models. The concept of joint optimization underpins cooperative game theory (seePeleg and Sudholter, 2003, for a survey) and also motivates a small but established literature at the intersection of noncooperative and cooperative game theory (see, for exampleAmbrus, 2009;Aumann, 1959;Bernheim et al., 1987;Konishi and Ray, 2003). However, despite the noted limitations of methodological individualism in economics (Arrow, 1994), the use of coalitional concepts in economics has not attained the same level of popularity as, for example, the use of the concept of beliefs, except insofar as the concepts of the household and the firm assume a sharing of intentions on the part of the individuals within those structures. The contrast is interesting, as developmental studies of children indicate that they collaborate at earlier ages than they can understand beliefs. One of the goals of the current paper is to show how a weakening of methodological individualism can lead to simple and striking economic predictions that flow from some of the deepest currents of human nature.Firm structure and designSo coalitional behavior can lead to heterogeneous choices by teams within a firm depending on their size. This effect is not necessarily monotonic. Large teams play the safe action, medium-size teams the risky action. In the absence of neighbors, small teams can easily solve the coordination problem and play the risky action, but the presence of neighbors playing safe is enough incentive for very small teams to choose the safe action.By exploiting the internal and external pressures that drive these results, a firm owner or manager can manipulate the structure of the firm to achieve desired outcomes. If the manager would like the safe action to be taken by a small workgroup, she will ensure it has strong links to a division that will definitely be playing the safe action typically a large department.On the other hand, if the manager would like a team to play the risky action this group could be the firms research group this team should be small and either have limited links to the rest of the firm, or only link to other teams that play the risky action.Entrepreneurs do indeed realize the potential cost of too much communication. AsSlone (2013)records, the founder of A, Jeff Bezos, has suggested“We should be trying to figure out a way for teams to communicate less with each other, not more”.An example of this maxim being put into practice is the Palo Alto Research Center (PARC), established by Xerox to create the innovations of the future. The PARC was deliberately geographically isolated from Xeroxs headquarters and existing research laboratory in New York. Given its intended role, it was important that the PARC was separated from the main bureaucratic processes and culture of Xerox, which was conservative and focused on its traditional copier business (Regani, 2005).Example: delayeringThere has been a trend in recent decades for organizations to shorten the lengths of their hierarchies. Moreover, many of these firms have also increased the span of control of the senior management group; there has been a notable increase in the number of individuals who directly report to the CEO. While there can be other drivers for such changes Guadalupe and Wulf (2010)emphasize the impact of product-market competition from internationalization here we useTheorem 2,Theorem 3to look at a possible relationship between watercooler chat and delayering.The elimination of Team C does not affect Team E, which is large enough that its decision to play the risky action cannot be outweighed by external influence. However, Team F is now in direct contact with Head Office, which plays the safe action. It follows from the third statement ofTheorem 3that all employees in Team F will also now play the safe action. The external contact here is crucial as it allows the senior manager to switch the behavior of a small unit.The analysis of this section shows how delayering can create opportunities for a principal to exercise her influence by creating different sized teams in her organization and linking them to create the right balance between external and internal pressures. In this way, different behavior can be generated in separate parts of an organization, whenever this is a required component of the organizations strategy.Example: job rotationFirms might choose to rotate workers through tasks for a variety of reasons. Here we show that rotation can act as a mechanism to allow the culture of one part of an organization to contage another part of the organization. Specifically, we show how even relatively short spans of time spent working in a small team can shape an employees behavior. When rotated back to a larger team, the employee will, for a while, retain the behavior to which he became accustomed in the small team. The periodic arrival of such employees is enough to change the long run culture of the large team from safe to risky.Now, from any state, the stateX=Ncan be reached without random shocks. To see this, consider that the following sequence of events will occur with positive probability. First, all current members of the small team meet at the small teams watercooler, where they will agree to play the risky action. Second, the members of the small team switch places, one by one, with members of the large team. This gives at least four members of the large team who are now playing the risky action. Third, the other four members of the large team meet at the large teams watercooler and agree to switch to the risky action. They are happy to do this as the remaining four members of the team are already playing the risky action. Finally, the new members of the small team all meet at the small teams watercooler and switch to the risky action. We have reached the stateX=N. All employees are playing the risky action.Concluding commentsWhile the boundaries of a firm are defined by its physical assets (Hart and Moore, 1990), social interactions between workers characterize the way things get done in an organization. Workers idly sharing scuttlebutt around the watercooler might seem like the bane of an employers life, but these informal interactions could engender collective actions that enhance firm productivity. This paper has examined how a manager can tinker with an organizations structure and the physical work environment to harness workers informal interactions for the firms advantage.Although the direct application considered in this paper is the design of a firm, it is clear that adaptive/evolutionary models that incorporate some degree of collective agency should also be applicable to other problems in applied economics. In particular, the implications of collective agency may be of particular importance whenever formal structures in an organization can facilitate informal interactions. This is true for academic conferences, where informal interactions are typically of more import than organized presentations, and also for diplomacy, where formal meetings are accompanied by informal, less structured, discussions in which parties are often more able to find common ground and create shared intentions.中文饮水机旁聊天，组织结构和企业文化乔纳森牛顿，安德鲁怀特，西蒙安格斯摘要将公司建模为员工网络，办公室里的偶尔协作决策会改变长期的员工行为（企业文化）。给定员工团队中出现的文化取决于团队规模以及团队与更广泛公司的联系方式。探索了该模型对组织结构的影响，并将其与层次结构设计的趋势相关联。关键字：合作，团队，层次结构，延迟，网络，演化苹果是一家纪律严明的公司，我们的流程非常好，但这不是主要的。流程使我们更高效，但是创新来自人们在走廊上聊天或晚上10:30互相交流产生的新想法苹果公司创始人史蒂夫乔布斯。引言当人们由共同的利益追求时，人们会互相交流，分享想法并进行协作。员工将他们的协作性带入工作场所，并与同事打交道，他们在车间，会议，生产线以及咖啡和午餐休息时间与他们进行互动。在本文中，我们考虑了工作场所社交环境中的协作决策，并使用简单的自适应决策模型表明，这可能对公司文化和组织的最佳内部结构产生巨大而深远的影响。我们的模型采用了有据可查的事实，即人类特别擅长互利合作（Tomasello，2014年），并将这一事实整合到了最佳响应动态的嘈杂变量中（Young，1998年），这一直是经济建模的基础。自古诺（1838）起。我们将公司建模为员工网络，每个员工都可以选择“安全”行动或“风险”行动。冒险行为代表了公司内部的创新行为，甚至是投机行为。员工只有在网络中足够多的邻居也这样做的情况下，才发现采取冒险行动符合他的利益。在公司内部，员工分为团队。团队是一群互相协作的员工，尽管他们也可能与团队之外的其他人互动。该团队代表员工的工作组，部门，甚至是公司董事会或高级管理委员会。员工参与协作行动选择的能力以“水冷却器”的概念为模型，冷却器使团队中的一小群员工可以聊天并形成协作意图。如果没有水冷却器，使员工无法分享意图，则该模型将简化为Young的规范模型，在该模型中，每个参与者选择安全行动的行为模式始终是长期均衡的（Peski，2010年）。当少数玩家偶尔在水冷却器上见面以形成共同的意图，协调他们的行动选择以达到共同的利益时，这种结果将不再成立。取而代之的是，通过将人性的基本面纳入模型中，我们可以根据网络拓扑获得多种行为。我们发现，为了使给定团队的成员在长期均衡中发挥冒险作用，必须满足一些条件。 （1）首先，团队不能太大。团队越大，围绕水冷却器进行的固定数量的协作决策对长期行为的影响的可能性就越小。 （2）其次，必须有足够数量的雇员在水冷却器上协调其战略选择；也就是说，团队内部的沟通必须足够强大，以产生足够的协作，以克服系统偏见，而采取安全行动。 （3）再次，团队规模不能太小，以免其成员的外部联系的影响导致他们采取安全行动，或者，如果团队确实如此小，则团队外部的所有成员联系都必须参加冒险行动的团队。换句话说，必须限制来自团队外部成员的外部影响。这些条件为组织设计提供了指导：它们可用于促进或预防组织不同部分的不同行为。这些条件中的每一个都有助于解释经验事实。条件（1）解释了为什么寻求促进创新的公司围绕小团队建立组织结构（Cook，2012； Stross，1996）。条件（2）有助于解释企业为增加自发性互动和促进工人之间的非正式沟通所付出的努力；也就是说，制造更大的水冷却器（Evans，2015年）。条件（3）有助于解释为什么组织要在团队中促进独立性，甚至将研究部门与组织的其他部分隔离开来（Sloan，1964）。文献综述本文对多方面的文献有所贡献。实际的贡献是关于工作场所社会环境的重要性的文献企业中工人之间互动的性质和模式（例如，参见Bandiera等，2005； Gibbons和Henderson，2013； Kandel和Lazear，1992）。我们证明了工作场所社会环境对集体代理的促进如何对公司文化产生重大影响。像Kreps（1990）和Hermalin（2001）一样，我们将企业文化建模为在协调博弈中发挥的均衡结果。为此，我们转向有关自适应决策和演化的文献，这使我们能够对企业文化的某些方面进行简单的解释，为范登斯汀（Van Den Steen）（2010）的共同信念模型提供替代，甚至互补的理论。进化模型通常关注长期均衡。这类似于关系契约文献如何将长期的民间定理应用于研究公司（Baker等人，1999; Levin，2003; Li等人，2017），不同之处在于进化模型对企业的合理性要求极低。如此低的理性模型已经成功地解释了实验室数据（Chong等，2006）以及经验现象，如农作物共享规范（Young and Burke，2001）和伊斯兰面纱的佩戴（Carvalho，2013）。当前的研究显示了将集体代理结合到这样的模型中如何在保持进化方法的简单性和优雅性的同时，可以导致更丰富的经验预测。将集体代理纳入扰动的演化动力学是一个相对较新且发展迅速的文献（Newton，2012； Newton，2012； Newton和Angus，2015； Sawa，2014； Serrano和Volij，2008），尽管在配对的背景下，成对偏差代表规模为2的联盟的有意行为（Jackson和Watts，2002; Klaus等，2010; Klaus和Newton，2016; Nax和Pradelski，2014; Newton和Sawa，2015）。人类参与集体代理的倾向性已得到充分证明，最近发展心理学的研究表明，合作的冲动是一种原始的冲动，这种冲动从14个月的年龄就开始显现出来（Tomasello，2014； Tomasello等，2005，Tomasello和Rakoczy，2003年）。最近的理论工作表明，在多种情况下，充当多元主体的能力将不断发展（Angus和Newton，2015； Newton，2017； Rusch，