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The purpose of this study is to identify how firms' sustainability performance is affected by external knowledge sources and absorptive capacity, accounting for the influence of being located in a science and technology park (STP).

Drawing on data from the Spanish Technological Innovation Panel, the authors estimate the determinants of sustainability performance using fixed effects multiple linear regression models with robust standard errors. The analysis covers the period 2009–2016, with a total panel of 8,874 companies and a total sample of 47,870 observations.

This study highlights the heterogeneity in on-park firms’ sustainability performance, which can be explained by the different capacities of these firms when it comes to embedding themselves in STP networks and processes and effectively absorbing the knowledge from the many knowledge sources that may be on offer in the park.

This paper contributes to the literature by examining the influence of external sources of knowledge and absorptive capacity, and the relationship between them, on sustainability performance. This study approaches sustainability performance as an aggregate measure of firms’ competitiveness and potential for long-term survival from the triple bottom line perspective. In addition, this study examines the effect that location in an STP can have on business sustainability performance and, more specifically, the mediating effect that knowledge sources and absorptive capacity can exert on this relationship.

Achieving good sustainability performance requires balancing higher economic profits with better environmental and social performance. Knowledge plays a key role in improving corporate sustainability performance, but this knowledge is becoming increasingly complex, specific and dispersed among many scientific, technological and business actors. Science and technology parks (STPs) are infrastructures designed to host varying types of organizations that can bring together new, disruptive knowledge. Our purpose is to unveil how these spaces can be drivers of sustainability performance for companies.

We test our hypotheses on a longitudinal database of Spanish companies over the period 2009–2016 using structural equation models (SEMs).

This research confirms that a firm’s location in an STP helps improve its sustainability performance, provided that conditions are optimal in the STP. These optimal conditions are based on an abundance of knowledge spillovers available to the firm and the firm’s ability to harness them, especially those of a more disruptive nature, through absorptive capacity.

Results of this study yield implications for academia in the form of future lines of research and practical implications for policymakers and managers of both STPs and the organizations that host them.

若要取得良好的可持續發展績效，我們必須以更佳的環境和社會績效來平衡更高的經濟利潤。知識在改善企業的可持續發展績效上發揮關鍵作用; 但知識對很多科學的、技術性的和商業的參與者來說，變得越來越複雜、特殊和分散。科技園是為集合嶄新而帶有顛覆性知識的各種不同組織提供軟硬體支援而設計的基礎設施。本研究擬顯露這些設施和場地如何能為企業推動其永續發展績效。

我們以結構方程模式、去測試有關涵蓋2009年至2016年期間西班牙企業的縱向數據庫的研究假設。

研究結果確認了只要在科技園內有最優良的環境和條件，企業在園內的位置是有助改善其永續發展績效的。這些最優良環境和條件是基於企業可得到的豐富的知識外溢，以及它們可透過其吸收能力去控制知識外溢的能力，特別是那些具更強顛覆性本質的知識外溢。

研究結果為學術界就未來的研究領域提供了啟示; 研究結果亦為科技園和主辦機構的政策制定者和經理、提供了實務方面的啟示。

Medical diagnosis and treatment processes exhibit a high degree of variability, as during the process execution, healthcare professionals can decide on additional steps, change the execution order or skip a task. Process models can help to document and to discuss such processes. However, depicting variability in graphical process models using standardized languages, such as Business Process Model and Notation (BPMN), can lead to large and complicated diagrams that medical staff who do not have formal training in modeling languages have difficulty understanding. This study proposes a pattern-based process visualization that medical doctors can understand without extensive training. The process descriptions using this pattern-based visualization can later be transformed into formal business process models in languages such as BPMN.

The authors derived patterns for expressing variability in healthcare processes from the literature and medical guidelines. Then, the authors evaluated and revised these patterns based on interviews with physicians in a Danish hospital.

A set of business process variability patterns was proposed to express situations with variability in hospital treatment and diagnosis processes. The interviewed medical doctors could translate the patterns into their daily work practice, and the patterns were used to model a hospital process.

When communicating with medical personnel, the patterns can be used as building blocks for documenting and discussing variable processes.

The patterns can reduce complexity in process visualization. This study provides the first validation of these patterns in a hospital.