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Rather than spend an inordinate amount of time and resources on planning what is inherently unknown and uncertain, socially-focused organizations like Panera Cares, Banco Davivienda, and Brigham Young University's (BYU) Design Exploration lab quickly map out their assumptions, run experiments to test those assumptions, and adjust their plans based on their learnings. In this article, we explain and expand on how organizations of all kinds (whether they be large corporations, social ventures, or government agencies) have bought into the idea of using innovation and experimentation for impact; and how despite recent advancements of design thinking on the social impact front, the actual implementation of innovative ideas remains elusive for many organizations. The article further presents a more systemic model for social impact innovation: social impact models, which provide one possible solution by enabling social ventures to achieve a more robust validation of their new- and not-so-new-to-the-world ideas by mapping and strategies by mapping out each assumption and iteratively testing them in the field. With this article, the authors seek to provide a practical process for how to apply the model, and how to avoid the most common illusory validation traps, which together would allow socially-focused organizations to more frequently succeed and deliver more impact with their endeavors.

In this article, we study how a Chinese real estate broker - Lianjia successfully transformed itself into Beike - China’s leading digital platform for housing transactions and services. We explain the motivation behind this platform transformation, how it turned out, and what are the lessons learned for other companies contemplating a platform transformation. Beike’s lessons are significant as they not only can help the companies achieve growth via platform transformation but also create social value by contributing to higher service quality in traditional service industries.

We draw upon comprehensive archival research into Beike, and our many years of ongoing research on platform strategy and business growth strategy.

This article provides important lessons for companies in traditional service industries on how to expand growth via digital platforms. We summarize four key lessons learned: 1) data is central to success in platform transformation; 2) industry knowledge and experience play an important role; 3) the right platform governance is critical in value creation; 4) harness the double powers of platform and digital transformation.

More research on digital platforms and platform transformation in traditional service industries is needed to delve into the underlying factors and delineate the boundary conditions for specific details in this strategy and implementation.

This article is useful to business executives, academics, management consultants, and entrepreneurs interested in learning more about how to use digital platforms to achieve business growth and create economic and social value. In particular, Beike’s case offers inspiration and valuable lessons to companies in traditional service industries and helps them consider the factors that are important in the process of platform transformation.

This article on Beike provides an innovative solution to business leaders in traditional service industries grappling with a lack of professional standards and trust to use digital platforms to elevate service quality and create social value.

This article is unique and add value because Beike is a pioneer of using the digital platform to achieve growth and transform traditional service industries. Our study shows that platform transformation not only can help a company in a traditional industry achieve impressive growth but at the same time can create enormous social value by elevating the service quality of the whole industry.

So far, the simplicity of heuristics has been mostly studied at the rule level. However, actors' bounded rationality implies that small bundles of rules drive behavior. This study thus conducts a conceptual elaboration around such bundling. This leads to reflections on the various processes of heuristic emergence and to qualifications of the respective characteristics of basic heuristic classes.

Determining which rules – out of many possible ones – to select in one's small bundle constitutes a difficult combinatorial problem. Fortunately, past research has demonstrated that solutions can be found in evolutionary mechanisms. Those converge toward bundles that are somewhat imperfect yet cannot be easily improved, a.k.a., locally optimal bundles. This paper therefore identifies that heuristic bundles can efficiently emerge by social evolutionary mechanisms whereby actors recursively exchange, adopt and perform bundles of rules constitute processes of heuristic emergence.

Such evolutionary emergence of socially calculated small bundles of heuristics differs from the agentic process by which some simple rule heuristics emerge or from the biological calculation process by which some behavioral biology heuristics emerge. The paper subsequently proceeds by classifying heuristics depending on their emergence process, distinguishing, on the one hand, agentic vs evolutionary mechanisms and, on the other hand, social vs biological encodings. The differences in the emergence processes of heuristics suggest the possibility of comparing them on three key characteristics – timescale, reflectivity and local optimality – which imply different forms of fitness.

The study proceeds as a conceptual elaboration; hence, it does not provide empirics. At a microlevel, it enables classification and comparison of the largest possible range of heuristics. At a macrolevel, it advocates for further exploration of managerial bundles of rules, regarding both their dynamics and their substantive nature.

In the field, practitioners are often observed to socially construct their theory of action, which emerges as a bundle of heuristics. This study demonstrates that such social calculations provide solutions that have comparatively good qualities as compared to heuristics emerging through other processes, such as agentic simple rules or instinctive – i.e. behavioral biology – heuristics. It should motivate further research on bundles of heuristics in management practice. Such an effort would improve the ability to produce knowledge fitting the absorptive capacity of practitioners and enhance the construction of normative managerial theories and pedagogy.

Bundles of rules may also play a crucial role in the emergence of collective action. This study contributes to a performativity perspective whereby theories can become reality. It demonstrates how the construction of a managerial belief system may amount to the launching of a social movement and vice versa.

Overall, many benefits accrue from integrating the bundles of rules expressed and exchanged by practitioners under the heuristic umbrella. So far, in management scholarship, such emergent objects have sometimes been interpreted as naïve or as indicative of institutional pressures. By contrast, this study shows that socially calculated bundles may efficiently combine the advantages of individuals' reflective cognitive processes with those provided by massive evolutionary exchanges. In conclusion, the social calculations of small heuristic bundles may constitute a crucial mechanism for the elaboration of pragmatic theories of action.

Ecosystem partnerships are driving a dramatic change in the nature of business as industries as diverse as banking, automotive and retail are converging in unprecedented ways–and at an unprecedented rate. To learn how leading companies are embracing innovation in ecosystems to drive both value creation and competitiveness, the IBM Institute for Business Value in collaboration with Oxford Economics surveyed 1000 top executives in 19 industries and 29 countries between August and January 2019.

The survey cohort included 250 Chief Executive Officers, 150 Chief Financial Officers, 150 Chief Innovation Officers, 150 Chief Marketing Officers, 150 Chief Operations Officer and 150 Chief Alliance/Partnership Officers.

Analysis revealed that organizations with high engagement in ecosystems generate greater revenues from innovation initiatives. Specifically, revenues tied to innovation were more than 14 percent higher for ecosystem-engaged businesses than their less ecosystem-oriented peers.

The analysis showed that organizations differentiated on four innovation-enabling dimensions are more successful than others in ecosystem innovation. Their winning practices: 10;•9;They lead with platforms for innovating in ecosystems. 10;•9;They create the structures that enable the transformation of ideas into desired customer experiences in ecosystems 10;•9;They establish effective, meaningful measurements for successful innovation in ecosystems. 10;•9;They approach innovation with a collaborative mindset and create an environment of openness that shapes innovative behavior. 10;

The study identified the best practices of the most successful companies, ecosystem innovators. They excel across four innovation dimensions. They build platforms and employ ecosystems to better orchestrate customer experiences. They establish processes to effectively measure innovation within ecosystems in which they operate. They form organizational structures that institutionalize innovation. And they create and promote environments of openness and collaboration

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.