外文文献翻译原文及译文
（节选重点翻译）
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：4100 多字
英文
Watercooler chat, organizational structure and corporate culture Jonathan Newton, Andrew Wait, Simon Angus Abstract
Modeling 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, Evolution Apple is a very disciplined company, and we have great processes. But that"s not what it"s 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. Introduction
People 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 since Cournot (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 employee"s 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 of Young, 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. Section 5 provides 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 literature
This 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 example Bandiera 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. Like Kreps (1990)and Hermalin (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 of Van
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 documented and 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 (see Peleg 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 example Ambrus, 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 design
So 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 firm"s 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. As Slone (2013) records, the founder of Amazon.com, 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 Xerox"s 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: delayering
There 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 use Theorem 2, Theorem
3 to 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
of Theorem 3 that 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 organization"s strategy. Example: job rotation
Firms 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 employee"s 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 state X=N can 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 team"s 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 team"s 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 team"s watercooler and switch to the risky action. We have reached the state X=N. All employees are playing the risky action. Concluding comments
While 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 employer"s life, but these informal interactions could engender collective
actions that enhance firm productivity. This paper has examined how a manager can tinker with an organization"s structure and the physical work environment to harness workers" informal interactions for the firm"s 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，2019）。本研究的作者认为，赞成将集体代理纳入人类行为模型的证据是压倒性的。此外，自适应/进化框架对此非常理想，因为与静态分析相反，它们明确地对处于平衡状态和处于平衡状态的行为进行建模。
最后，我们注意到在进化动力学中关于集体代理的工作建立在关于博弈论模型中的联盟行为的更广泛文献上。联合优化的概念是合作博弈理论的基础（参见 Peleg 和 Sudholter，2003，进行调查），
并且在非合作博弈和合作博弈的交叉点上激发了一些既小却已确立的文献（例如，参见 Ambrus，2009； Aumann，1959； Bernheim 等，1987； Konishi 和 Ray，2003）。然而，尽管方法论个人主义在经济学中有明显的局限性（Arrow，1994），但在经济学中使用联盟概念并没有达到与使用信念概念相同的普及水平，除了在概念上住户和企业中的一部分承担了这些结构中个人的意图共享。这种对比很有趣，因为对儿童的发育研究表明，他们的协作年龄比他们理解的信念还早。本文的目标之一是说明方法论上的个人主义的弱化如何导致简单而引人注目的经济预测，这些预测来自人性的某些最深层次的潮流。
公司结构设计
因此，联盟行为可能导致公司内部团队根据规模进行异类选择。此效果不一定是单调的。大型团队采取安全行动，中型团队采取风 险行动。在没有邻居的情况下，小团队可以轻松地解决协调问题并 采取冒险行动，但是有邻居在场的人安全行事足以激励很小的团队 选择安全的行动。
通过利用驱动这些结果的内部和外部压力，公司所有者或经理可以操纵公司的结构以实现期望的结果。如果经理希望由小型工作组采取安全措施，则她将确保该工作组与肯定会采取安全措施的部门（通常是大型部门）具有紧密的联系。另一方面，如果经理希望团队进行冒险行动-这个小组可以是公司的研究小组-这个小组应该很小，或者与公司其他部门的联系有限，或者只与其他团队联系扮演
冒险的角色。
企业家确实确实意识到过多交流的潜在成本。根据
Slone（2013）的记录，Amazon.com 的创始人 Jeff Bezos 建议 “我们应该设法找到一种使团队之间相互交流更少而不是更多交流的方式”。
施乐公司已建立了这一准则，这是施乐（Xerox）建立的帕洛阿尔托研究中心（PARC），旨在创造未来的创新成果。
PARC 的地理位置故意与施乐总部和纽约现有的研究实验室隔离。鉴于其预期的作用，将 PARC 与施乐的主要官僚程序和文化区分开是很重要的， 施乐的文化是保守的，并且侧重于其传统的复印机业务 （Regani，2005 年）。示例：延迟 最近几十年来，组织一直在缩短其层次结构的长度。此外，这些公司中的许多公司还增加了高级管理团队的控制范围。直接向首席执行官汇报的个人数量显着增加。尽管还有其他推动因素，例如Guadalupe 和 Wulf（2010）强调了国际化对产品市场竞争的影响， 但在这里我们使用定理 2，定理 3 来研究水冷器聊天与延迟之间的可能关系。
淘汰 C 队不会影响 E 队，因为 E 队足够大，因此其采取冒险行动的决定不会因外部影响而超过。但是，F 团队现在与总公司直接联系，这是安全的行动。根据定理 3 的第三条陈述，F 团队的所有员工现在也将扮演安全的角色。外部联系人在这里至关重要，因为
它允许高级经理切换小型单位的行为。
本节的分析表明，延迟分配可以通过在组织中创建不同规模的团队并将其联系起来以在外部和内部压力之间建立适当的平衡，从而为校长创造机会来发挥其影响力。这样，只要这是组织策略的必要组成部分，就可以在组织的各个部分中生成不同的行为。
示例：工作轮换
企业可能出于各种原因选择轮流执行任务。在这里，我们表明轮换可以作为一种机制，使组织的某个部分的文化融合到组织的另一部分。具体来说，我们展示了在一个小团队中花费相对较短的时间会如何影响员工的行为。当轮换回到较大的团队时，员工将在一段时间内保留他在小型团队中习惯的行为。这些员工的定期到来足以将大型团队的长期文化从安全变为风险。
现在，从任何状态开始，都可以在没有随机冲击的情况下达到 状态 X = N。要看到这一点，请考虑以下事件序列将以正概率发生。首先，小团队的所有现有成员都在小团队的水冷却器上开会，他们 将同意扮演冒险的角色。其次，小团队的成员与大团队的成员一一 交换位置。这使大型团队中至少有四名成员正在冒险。再次，大型 团队的其他四名成员在大型团队的饮水机见面，并同意转而采取冒 险行动。他们很高兴这样做，因为团队的其余四名成员已经在冒险。最后，小团队的新成员都在小团队的水冷却器上见面并转向冒险行 动。我们已经达到状态 X = N。所有员工都在冒险。
结论
虽然公司的边界由其有形资产定义（Hart 和 Moore，1990），但工人之间的社会互动是组织中事物完成方式的特征。工人在水冷却器周围闲逛时，雇主似乎并不喜欢这样，但是这些非正式的互动可能会创新企业文化，从而提高公司的生产率。本文研究了经理如何修改组织的结构和实际工作环境，以利用工人的非正式互动来获得公司的利益。
尽管本文考虑的直接应用是公司的设计，但很明显，包含一定程度的集体代理的自适应/进化模型也应适用于应用经济学中的其他问题。特别是，只要组织中的正式结构可以促进非正式的互动，集体代理的含义就可能特别重要。对于学术会议和非正式会议来说， 这是正确的，在学术会议中，非正式互动通常比有组织的演讲更为重要；在外交会议中，正式会议伴随着非正式的，结构性较小的讨论，在这些讨论中，各方通常更有能力找到共同点并建立独有的企业文化。