Moments of crisis may serve as critical junctures for imagining alternatives. As the future has become increasingly volatile and precarious in these unsettled times of pandemic, climate emergency, rising inequality and an ever looming digital (r)evolution, there is a great need and opportunity to develop theory that can guide society towards its future potentialities. But how can we theorize what does not (yet) exist? A central task would be to develop methodological strategies that make the future amenable to empirical study. This is quite ambitious. In this essay we seek to take one of many steps and advocate for such (re-)search for the future, where acts of (disciplined) imagination become input for theory building.

Calls abound for us management scholars to assume a more engaged societal role by breaking away from a narrow, paradigm-driven ‘theory fetish’ and instead, contribute to solving grand challenges and societal problems (Biggart, 2016). We do not see this as an either/or. It is time for us as management scholars to use the methodological and theoretical toolkit at our disposal to co-create the future; and to actively feed forward soci(et)al change – not despite theory, but through it.

However, the future poses some peculiar problems: By definition, it is not here yet. Thus, the quest to contribute to the construction of a future social reality by theorizing it raises some fundamental questions: Do we actually need to wait until something exists before we can build theories about it? Or can we ex ante theorize a post-COVID-19 world or think through the consequences of a society radically shaped by artificial intelligence? To put it differently, the conundrum we face is the following: As an empirical social science, management scholarship deals with the social world as it exists and came to be; our methodological tools are based on data sourced from observable events that have already occurred. Thus, how can we study, conceptualize, and theorize what is not (yet) observable and does not (yet) exist? Could we indeed build valid theories based on acts of imagination?

When management scholars engage with the future, their aim is commonly to anticipate possible futures through predictive analysis. But anticipating or predicting a probable future is not our aim. Instead, we seek to articulate desirable futures, and how they might become reality. There are two reasons for this. First, our analytic capabilities to predict the future will likely be dwarfed by the predictive strength of corporate research. Big technology companies like Alphabet, Amazon, Facebook, Apple, and Microsoft employ thousands of researchers to analyse masses of data, often routinely harvested as a by-product of digital traces for machine learning. As a result, the methodological innovations needed to describe, analyse, and predict human behaviour are no longer championed by academic scholars but by capitalist institutions whose aim it is to generate profits (Savage and Burrows, 2007). Their increasingly powerful methods turn behavioural data into what Shoshana Zuboff calls ‘prediction products’ that not only predict our behavioural futures but also intervene in them. Outperformed by corporate research, we may find ourselves subjected to profitable but dystopian future developments.

Second, predicting the future is not (good) enough. Rather than trying to compete over who can make better predictions and build better models, we need to reclaim our societal relevance by redefining our purpose in engaging with the future altogether. A central aim must be to create more desirable futures. However, the prevailing approaches to predicting or anticipating the future in management studies lack such a critical reflection on their normative orientation. For instance, scenario planning is a popular heuristic tool in strategic management that primarily aims at generating various plausible scenarios for emerging futures. But it is precisely the elaboration, critical reflection, and theorizing on futures that are not just plausible and probable but also desirable where we believe that scholarship can make a difference and reclaim its societal relevance. Rather than extrapolating to future states of the world from our present, what we also need is research guiding normative conceptions of the future. The aim would be to create new future visions – strengthened through theory – that open up radically new prospects for human agency to shape the world.

This ambition poses an obvious methodological difficulty: If the aim is to open up future potentialities that break away from the present, how can we do this using the tools of scientific analysis? The methodological challenge we hence face is to generate critical knowledge for the future with data sourced from the present. As social scientists, we commonly study the social structures of our prevailing era (Abbott, 2001). Empirical data exists as soon as the phenomenon of inquiry has happened. Thus, data gathering and analysis is backward looking. The predominant institutional infrastructures and settled practices that we examine also constrict, limit and in fact imprison our thinking and theorizing. But we want to look forward. And to do so, we need to free ourselves from our own cognitive and methodological chains. Can we do so while maintaining standards of academic rigor?

危机时刻可能成为想象替代方案的关键时刻。在大流行、气候紧急情况、不平等加剧和日益迫在眉睫的数字（r）演变的动荡时期，未来变得越来越不稳定和不稳定，因此非常需要和机会来发展能够引导社会走向未来潜力的理论。但是，我们如何才能将（尚）不存在的东西理论化？一项中心任务是制定方法策略，使未来适合实证研究。这是相当雄心勃勃的。在这篇文章中，我们寻求采取许多步骤之一，并倡导这种（重新）对未来的探索，其中（有纪律的）想象行为成为理论构建的输入。

呼吁我们管理学者通过摆脱狭隘的、范式驱动的“理论迷信”来承担更多参与的社会角色，转而为解决重大挑战和社会问题做出贡献（Biggart，2016 年）。我们不认为这是非此即彼的。是时候让我们作为管理学者使用我们掌握的方法论和理论工具包来共同创造未来了；并积极推动社会（等）变革——尽管有理论，但通过理论。

然而，未来会带来一些特殊的问题：根据定义，它还没有到来。因此，通过理论化构建未来社会现实的探索提出了一些基本问题：我们是否真的需要等到某物存在才能建立关于它的理论？或者，我们是否可以事前对 COVID-19 后的世界进行理论化，或者思考一个由人工智能彻底塑造的社会的后果？换句话说，我们面临的难题是：作为一门实证社会科学，管理学研究处理社会世界的存在和形成；我们的方法工具基于来自已经发生的可观察事件的数据。因此，我们如何研究、概念化、并理论化什么（尚未）可观察且（尚）不存在？我们真的可以建立基于想象行为的有效理论吗？

当管理学者与未来打交道时，他们的目标通常是通过预测分析来预测可能的未来。但预测或预测一个可能的未来并不是我们的目标。相反，我们寻求表达可取的未来，以及它们如何成为现实。有两个原因。首先，我们预测未来的分析能力可能与企业研究的预测能力相形见绌。Alphabet、亚马逊、Facebook、苹果和微软等大型科技公司雇佣了数千名研究人员来分析大量数据，这些数据通常作为机器学习数字轨迹的副产品而收集。因此，描述、分析和预测人类行为所需的方法创新不再受到学术学者的支持，而是受到旨在创造利润的资本主义机构的支持（Savage and Burrows，2007）。他们越来越强大的方法将行为数据转化为 Shoshana Zuboff 所说的“预测产品”，不仅可以预测我们的行为未来，还可以干预它们。在企业研究方面表现出色，我们可能会发现自己受到有利可图但反乌托邦的未来发展的影响。

其次，预测未来还不够（好）。与其竞争谁能做出更好的预测和建立更好的模型，我们需要通过重新定义我们与未来完全接触的目的来恢复我们的社会相关性。一个中心目标必须是创造更理想的未来。然而，管理研究中预测或预测未来的流行方法缺乏对其规范方向的批判性反思。例如，情景规划是战略管理中一种流行的启发式工具，主要旨在为新兴的未来生成各种合理的情景。但恰恰是精雕细琢，批判性反思，在我们相信学术可以发挥作用并恢复其社会相关性的情况下，对不仅合理和可能而且也是可取的未来进行理论化。与其从我们的现在推断世界的未来状态，我们还需要研究指导未来的规范性概念。其目的是创造新的未来愿景——通过理论加强——为人类机构塑造世界开辟全新的前景。

这种雄心提出了一个明显的方法论困难：如果目标是打开脱离现在的未来潜力，我们如何使用科学分析工具来做到这一点？因此，我们面临的方法论挑战是利用来自现在的数据为未来生成关键知识。作为社会科学家，我们通常研究当今时代的社会结构（Abbott，2001）。探究现象一发生，经验数据就存在。因此，数据收集和分析是向后看的。我们考察的主要制度基础设施和既定实践也限制、限制并事实上禁锢了我们的思维和理论。但我们想向前看。为此，我们需要将自己从自己的认知和方法链中解放出来。我们可以在保持学术严谨标准的同时做到这一点吗？