學術論文

We investigate whether short interest affects supply chain partners' investments. This investigation is important for understanding the real effect of short sellers in facilitating stakeholders' investment decisions. Prior research suggests that short interest conveys negative news in a timely manner, which predicts future deterioration in firm fundamentals. We predict and find that a supplier's future investments decrease with its major customers' short interest. Consistent with predictions, this result is more pronounced when customers' short interest is more informative about their future performance, when customers have a more opaque information environment, and when suppliers incur lower customer switching costs. The results are robust when we use various approaches to address endogeneity concerns and establish causality. Our findings suggest that short sellers provide valuable information to supply chain partners when making investment decisions.

Interorganizational projects often suffer disruptions that require participating organizations to adapt in order to restore project operations. We study the role of communication style in facilitating adaptation to such disruptions. Whereas the literature on interorganizational communication has emphasized communication mode and frequency, we study the content and features of written communication in seven U.K. construction projects. Communication style mattered for adaptation quality in these projects, and we found that several properties of communication style were particularly important for adaptation: cost and information orientation, as well as informality, precision and authenticity. Moreover, managerial slack and organizational reputation were important precursors of communication style. These results provide novel insights into the role of communication style in adaptation to interorganizational project disruptions. We discuss the implications of these insights for research on interorganizational projects in operations and supply chain management.

這項研究指出公司的債務會削弱員工相關獎勵及損害士氣。我們建立了一個動態模型，研究一名經理運用有限的財政資源，同時向債權人還款及激勵員工士氣。若該名經理可以轉移或不正當地使用公司收入，公司的債務會減低員工達成既定獎勵目標的意欲，導致其工作效率降低。在平均利潤最大化的情況下，公司按優次償還債務，使員工的工作效率及工資逐步提升。即使公司已完全還清債務，此動態仍會持續。此外，我們發現一間公司的財務槓桿與激勵員工士氣的措施、工資及生產力屬反比關聯，這與動態模型的分析相符。

Building on the behavioral theory of the firm and institutional view, we examine how performance feedback (i.e., a focal firm’s performance relative to its industry peers) affects export intensity and how institution-related factors moderate this relationship. Using a sample of Chinese private manufacturing firms, we find that positive performance feedback lowers export intensity while the relationship between negative performance feedback and export intensity is insignificant. Moreover, outperforming firms are likely to decrease their export intensity even more when they are located in regions of better institutional development or have political connections. Underperforming firms with political connections tend to increase their export intensity. These findings enrich our understanding of the export behavior of emerging market firms.

為了保持競爭力，高科技製造商不僅經常從供應商採購新技術，也需向供應商提供資金援助以便他們能盡快將新技術轉化為可用的部件或生產工具。我們的研究關注以下情形。一個製造商考慮向一家財政拮据的供應商採購一項全新但未發展成熟的技術，或僅當新技術開發失敗時，才向現有供應商採購基於一項成熟技術的部件。製造商可以選擇以股權或貸款的形式注資來支持開發新技術。製造商需要對投資策略作出取捨，因為這不但會影響新供應商的努力水平和成功概率，還會影響現有供應商改進成熟技術的努力。正如債務融資文獻所述，我們發現貸款投資策略會因為供應商的有限責任而伴隨成本轉移效應，因此通常會提升新技術成功的概率。然而，由於製造商與新供應商之间除了有投資关系以外，也有採購关系，因此我們發現股權投資策略會伴隨利潤分享效應，而這一點在傳統的股權發行文獻中未有提及。若新供應商技術實力雄厚，利潤分享效應會勝過成本轉移效應並帶來更高的技術成功概率。然而，我們亦發現提高技術成功概率的策略未必會為製造商帶來更高的回報。一方面，成本轉移效應令製造商能在維持一定程度的技術成功概率的同時實現更低的採購成本，因此即使貸款策略會導致技術成功概率較低，但仍會成為製造商採用的方案。另一方面，當現有供應商能有效降低成本時，利用貸款來支持開發新技術或會引致新供應商過度努力而現有供應商努力不足，因此適得其反。

當代資訊科技(IT) 項目團隊要求成員提供新穎想法並加以落實，以應對不斷變化的資訊科技和業務需求。另外，新冠疫情限制商務出行，更多的公司必須允許有多學科背景的、分佈在多個地點的IT人才組成項目團隊來開發新的IT解決方案。在這個團隊，個體成員需要在創意構思(IG) 階段利用與他人不同的專業知識提出新穎的想法，然後在創意實施(II) 階段加以落實，這稱為IGII過程。儘管已有很多研究解釋個人創造力，但現存文獻甚少提供理論支撐以闡釋如何應對職能專長差異性和地理位置分散度所帶來的雙刃效應——它們是多學科、跨地域IT項目團隊的兩個基本特質，並與個人創造力和後續績效息息相關。我們借鑒IGII 框架，提出以交互記憶系統(TMS) 作為合理的團隊級解決方案以應對這挑戰。經由對35個IT項目團隊的141名成員及其主管集成的跨層次數據集進行分析，我們發現在跨學科、跨地域分佈的IT 項目團隊中，項目團隊級的TMS 和地理位置分散度會以交互方式調節團隊成員個人的IGII 過程，但在II 和IG兩個階段呈現出有趣的迥異性。

Problem definition: Providing fast and reliable delivery services is key to running a successful online retail business. To achieve a better delivery time guarantee policy, we study how to estimate and promise delivery time for new customer orders in real time. Academic/practical relevance: Delivery time promising is critical to managing customer expectations and improving customer satisfaction. Simply overpromising or underpromising is undesirable because of the negative impacts on short-/long-term sales. To the best of our knowledge, we are the first to develop a data-driven framework to predict the distribution of order delivery time and set promised delivery time to customers in a cost-effective way. Methodology: We apply and extend tree-based models to generate distributional forecasts by exploiting the complicated relationship between delivery time and relevant operational predictors. To account for the cost-sensitive decision-making problem structure, we develop a new split rule for quantile regression forests that incorporates an asymmetric loss function in split point selection. We further propose a cost-sensitive decision rule to decide the promised delivery day from the predicted distribution. Results: Our decision rule is proven to be optimal given certain cost structures. Tested on a real-world data set shared from JD.com, our proposed machine learning–based models deliver superior forecasting performance. In addition, we demonstrate that our framework has the potential to provide better promised delivery time in terms of sales, cost, and accuracy as compared with the conventional promised time set by JD.com. Specifically, our simulation results indicate that the proposed delivery time promise policy can improve the sales volume by 6.1% over the current policy. Managerial implications: Through a more accurate estimation of the delivery time distribution, online retailers can strategically set the promised time to maximize customer satisfaction and boost sales. Our data-driven framework reveals the importance of modeling fulfillment operations in delivery time forecasting and integrating the decision-making problem structure with the forecasting model.

我們研究當電動汽車充電設施的供應及需求可能存在空間錯配時，政府應如何制定資助政策，以有效地推動電動汽車的普及。電動汽車充電基礎設施通常由第三方服務供應商興建。雖然大多數電動汽車司機因通勤模式及市中心的便利性，更喜歡在市中心使用電動汽車充電設施，但服務供應商為了降低成本以獲取最大利潤，偏向把充電設施建於郊區。兩者對充電設施位置的偏好差異，導致電動汽車充電的整體成本高昂及電動汽車普及率偏低。我們使用簡化的博弈論模型，比較三種類型的資助政策：（i）購買電動車補助計劃，（ii）按充電設施的使用情況資助服務供應商，以及（iii）按充電設施數量資助服務供應商。我們發現，購買電動車補助計劃能有助推動電動汽車的普及，但未能緩解空間錯配的問題。相比之下，資助服務供應商可更有效地解決空間錯配的問題，並促進電動汽車普及。不過，統一按數量資助充電設施會令空間錯配的問題加劇，結果適得其反。在不同的情況下，每項政策都有可能成為最合適的對策，而應資助哪一方（服務供應商還是購買電動汽車的消費者），很大程度上取決於充電設施市場的成本考量，而非電動汽車價格或環境效益。我們提出一種“拼圖塊分區規則” 來作為制定政策的指引。我們主要考慮兩個維度：電動汽車司機的充電成本（主要包括搜尋和耗時）和充電設施的建設成本在不同地區的差異。在一端，如果充電太耗時，或設施太少、太擁擠，則首選資助負責興建的服務供應商；在另一端，若充電服務方便快捷的話，則首選資助購買電動汽車的消費者；在中间充電成本適中的情況下，只有在市中心興建充電站的費用較郊區稍高一些時，資助服務供應商才是首選。

This paper provides a general analysis of signaling under double-crossing preferences with a continuum of types. There are natural economic environments where the indifference curves of two types cross twice, such that the celebrated single-crossing property fails to hold. Equilibrium exhibits a threshold type below which types choose actions that are fully revealing and above which they pool in a pairwise fashion, with a gap separating the actions chosen by these two sets of types. The resulting signaling action is quasi-concave in type. We also provide an algorithm to establish equilibrium existence by construction.