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The purpose of this paper is to synthesize ten years of case studies and data analysis from which emerged an organizational design that facilitates adaptability, agility, and resilience. The resulting triangular model of culture, leadership, and systems is proposed.

Analysis of over 100 case studies over ten years along with statistical analysis of survey data from 50 of those companies resulted in the emergence the triangular model and provides quantitative support for validity.

People drive a complex and dynamic system with culture, leadership, and systems as key factors driving organizational success in a rapidly changing environment. The critical factor in adapting to change is designing organizations to maximize the vast tacit knowledge base within organizations. Diagnostic tools are necessary to identify underlying strengths and weaknesses to initiate targeted discussions and provide a baseline for measurement.

All of the organizations were from Europe, Africa, or the Middle East.

The emergent people-centric triangular model with culture, leadership, and systems at the points along with the development of a diagnostic tool offers a methodology for executives to gain valuable insight into critical elements of their organizations from which to initiate constructive dialogue leading to effective action.

Many authors have offered theories on developing agile organizations. The emergent people-centric performance triangle and evolving diagnostic instrument add to the body of existing literature and lays the groundwork for practical tools and methods to yield practical results.

The purpose of this paper is to provide a conceptual model for the transformation of big data sets into actionable knowledge. The model introduces a framework for converting data to actionable knowledge and mitigating potential risk to the organization. A case utilizing a dashboard provides a practical application for analysis of big data.

The model can be used both by scholars and practitioners in business process management. This paper builds and extends theories in the discipline, specifically related to taking action using big data analytics with tools such as dashboards.

The authors’ model made use of industry experience and network resources to gain valuable insights into effective business process management related to big data analytics. Cases have been provided to highlight the use of dashboards as a visual tool within the conceptual framework.

The literature review cites articles that have used big data analytics in practice. The transitions required to reach the actionable knowledge state and dashboard visualization tools can all be deployed by practitioners. A specific case example from ESP International is provided to illustrate the applicability of the model.

Information assurance, security, and the risk of large-scale data breaches are a contemporary problem in society today. These topics have been considered and addressed within the model framework.

The paper presents a unique and novel approach for parsing data into actionable knowledge items, identification of viruses, an application of visual dashboards for identification of problems, and a formal discussion of risk inherent with big data.

The ability to make good decisions is the defining attribute of a high performance organization. The challenge is to ensure that good decision‐making practices permeate the entire organization. As organizations grow, employees make decisions in an increasingly complex, ambiguous, and uncertain environment. Formal practices enable employees to make decisions that are meaningful to the firm's stakeholders and guide their behaviours to align with the strategic intent of the firm as well as its values and norms.

Through case studies and consultancy work the author has developed an approach to focus on management decision making and improved effectiveness.

This paper describes a diagnostic tool which helps companies understand how well their management systems support decision making and where CEOs should invest to focus leadership time and attention. The decision‐making scorecard and tools help CEOs design effectiveness management systems and focus its use to drive their specific business agenda.

With formal decision‐making practice in place, CEOs rely on delegation and control practices to ensure that employees make decisions in line with the organization's vision and values. Using the described approach, CEOs and employees focus their attention on the relevant control levers and use their time for interaction and learning rather than control. Furthermore they successfully apply more relevant decision‐making practices than before, and have abandoned extensive and expensive performance management projects in favour of more differentiated and focused initiatives that support their immediate goals with a direct impact. The tools have been used to ensure that the next strategic move delivers the expected value. In summary, good decision‐making practices translate the CEOs' power and responsibility into higher performance, growth and lower risk.

The purpose of this paper is to uncover the desired qualities and behaviours that patients believe general practitioners (GPs) should have in medical (service recovery) encounters. In particular, the authors try to reveal the qualities and behaviours of GPs that patients value, to understand the underlying benefits that they look for during personal (service recovery) encounters, and to graphically illustrate the findings in a so‐called hierarchical value map. This will prove to be important in order to understand patients' needs and desires correctly.

An exploratory research study using the qualitative laddering interviewing technique was regarded as appropriate as it allows researchers to gain a deeper insight into an underdeveloped research subject. In total, in‐depth laddering interviews with 38 respondents were conducted.

In case of a service recovery encounter, patients believe that GPs need to show competence, friendliness and empathy in order to restore trust in them. GPs should also listen actively and do the appropriate checks in order to find the root cause of the problem. “Health” was the main value sought by patients. This value is considered by patients to be the gateway to moving on with their everyday lives and search the attainment of other values such as well‐being, belongingness, accomplishment, and self‐realization. Moreover, respondents would like to gain knowledge about their disease in order to prevent them in the future and to have some sense of control over the decision of the treatment. Patients also want a more active role in the medical (service recovery) encounter, which calls for a more shared approach by GPs in the interaction with their patients.

This paper gives a valuable first insight into the desired qualities and behaviours of GPs during medical (service recovery) encounters. The study results especially indicate that complaining patients are people first and patients second, where the primary importance is the satisfaction of basic social needs. The fact that this study has revealed the highest number of values in published laddering studies so far shows how crucial these medical (service recovery) encounters in general and GP qualities and behaviours in particular are for patients. Another strong contribution of this paper is the finding that all the identified concepts from the laddering interviews that are shown in the hierarchical value maps must not been seen in strict isolation, as in previous research, but have to be understood as a network of interrelated concepts.

Understanding how individuals respond and adapt to change is essential to assist leaders to manage transformational change effectively. Contemporary health care environments are characterised by frequent and rapid change, often with unrealistic and challenging timeframes. Researchers have employed a range of assessment scales to assess individual readiness for change. Hence, to select the appropriate scale, it is critical to compare the properties of these instruments. A scoping review will be conducted to identify scales that measure an individual's response to change in the healthcare environment.

In this article the authors used the PIC (Population or Problem, Interest, and Context) design and undertook a comprehensive literature search conducted in Eric, MEDLINE, EmCare, CINAHL, PsychINFO and PubMed. Management databases were also searched including Business Source Premium (Ebesco) and Business Collection (InfoRMIT). Reference lists were scrutinized, and citation searches were performed of the included studies. The primary outcome was the quality of the literature searches and the secondary outcome was time spent on the literature search when the PIC model was used as a search strategy tool, compared to the use of another conceptualizing tool or unguided searching.

This scoping review identified eight scales used to measure an individual's response to change. This scoping review did not identify any individual change readiness scales specifically designed for use in the healthcare environment. However, two scales (the Acceptance of Change Scale and the Resistance to Change Scale) had applicability across a wide variety of organisational settings.

Scoping reviews do not set out to comprehensively source all relevant literature but rather to ascertain the nature and extent of the published literature in the field. Therefore, it is possible that a systematic review might uncover additional relevant papers.

This scoping review will assist change leaders to gain a better understanding of the different scales used to measure individual response to change.

To manage change effectively, change leaders first need to develop an understanding of how individuals respond and adapt to change. Change leaders require the necessary scales to assist them to understand change processes, providing an understanding of where individuals are placed on the change continuum. To the best of the authors' knowledge, this scoping review is the first of its kind to identify and review scales to measure individual response to change.

The purpose of this paper is twofold: first, to examine whether polychronicity, an individual difference variable that involves a preference for multitasking, moderates the relationships between work-family conflict (WFC) and two work criteria, job satisfaction and work engagement; second, to examine two measures of polychronicity (the multitasking preference inventory (MPI) and the inventory of polychronic values (IPV)) and investigate whether polychronicity moderates the relationships between WFC and work criteria differently when measured by the MPI or the IPV.

The study’s sample included 257 respondents from the Amazon Mechanical Turk service who completed an online survey. Multiple regression analyses were conducted to test whether polychronicity moderated the relationships between WFC and two work criteria, job satisfaction and work engagement.

Polychronicity was found to significantly moderate the relationship between the work engagement and WFC. Follow-up analyses indicated that those who were lower in polychronicity had a significant decrease in work engagement as WFC increased, whereas those who were higher in polychronicity had relatively the same work engagement level regardless of changes in WFC. The results suggest that individuals higher in polychronicity have more personal resources and may be more resilient than those lower in polychronicity when it comes to not letting conflicts between their work and family lives affect how engaged they feel in their work.

This study extends the application of polychronicity to new domains of WFC and work engagement. The current study also contributed to the literature by investigating two measures of polychronicity (MPI and IPV) and finding that the MPI significantly moderated the relationship between WFC and work engagement, but the IPV did not. These findings indicate that there are important differences between the MPI and the IPV, and additional research is needed in comparing these two polychronicity measures.

An increasing number of migrants and refugees seeking asylum in Germany is challenging psychiatrists and psychotherapists in multiple ways. Different cultural belief systems on the causes of mental illness and their treatment have to be taken into consideration. The purpose of this study is to explore perceived causes of depression among Farsi-speaking migrants and refugees from Afghanistan and Iran, which represent two groups with a shared cultural heritage, but originating from very different regimes of mobility. Both are among the largest migrant groups coming to Germany over the past decade.

In total, 50 Iranian and 50 Afghan migrants and refugees, who arrived in Germany in the past 10 years were interviewed, using an unlabeled vignette presenting signs and symptoms of depression. The answers were then coded through inductive content analysis.

Among Iranians, there was a more significant number of causal attribution to Western psychiatric concepts, whereas Afghans attributed depression more often to the experience of being a refugee without referring to psychological concepts. These differences in attribution did, however, not affect the desire for a social distance toward depressed people. Nonetheless, a higher number of years spent in Germany was associated with less desire for social distance toward persons with depression among Afghans, but not among Iranians.

To the best of the knowledge, this is the first study examining perceived causes of depression with Farsi-speaking migrants in Germany and contributes to understanding tendencies in the perception of depression in non-Western migrant groups.

The purpose of this empirical case study is to apply several existing frameworks to consider the notion of integrating corporate social responsibility (CSR) with a brand leadership strategy. The investigation focuses on two main questions: What are the core components for the development of a CSR brand? What capabilities are necessary to implement a CSR‐related brand strategy?

Five firms provide input for a multiple case‐based approach.

Intuitive and intended approaches for CSR brand leadership emerge from the multiple case study results. Different capabilities are required at each stage of the development and implementation process for CSR brand leadership.

This research extends three prior studies – Aaker and Joachimsthaler's brand leadership framework, Maon et al.'s proposed integrative framework for designing and implementing CSR, and Beverland et al.'s capabilities view on the development of global brand leadership – and fills a theoretical gap.

Managers can use the proposed integrated and implementable framework to determine the impact of dynamic factors, such as ownership, culture, executive leadership, and the specific context of product and corporate branding, on the development and implementation of their CSR brand.

No studies examine how to leverage CSR in brand‐building activities. Specifically, no empirically grounded research examines the required path to create and manage CSR brands and associated benefits, nor is the number of capabilities required to develop a credible CSR brand clear. Comprehensive models of the processes for developing and implementing CSR brands and the capabilities that underlie them are needed. The proposed model emphasizes the contextualized need to rely on different capabilities at different stages of this development process to generate constructive and sustainable outcomes.

In recent years patents have become a very popular data source for forecasting technological changes. However, since a vast amount of patents are “worthless” (Moore, 2005), there is a need to identify the promising ones. For this purpose, previous approaches have mainly used bibliographic data, thus neglecting the benefits of textual data, such as instant accessibility at patent disclosure. To leverage these benefits, this study aims to develop an approach that uses textual patent data for predicting promising patents.

For the identification of promising patents, the authors propose a novel approach which combines link prediction with textual patent data. Thereby the authors are able to predict the emergence of hitherto unmentioned bigrams. By mapping these future bigrams to recent patents, the authors are able to distinguish between promising and nonpromising patents. To validate this approach, the authors apply the methodology to the case example of camera technology.

The authors identify stochastic gradient descent as a suitable algorithm with both a receiver operating characteristic area under curve score and a positive predictive value of 78%, which outperforms chance by a factor of two. In addition, the authors present promising camera patents for diverse application fields, such as cameras for surgical systems, cameras for rearview vision systems in vehicles or light amplification by stimulated emission of radiation detection and ranging cameras for three-dimensional imaging.

This study contributes in at least three directions to scholarship. First, the authors introduce a novel approach by combining link prediction with textual patent analysis and, in this way, leverage the benefits of both worlds. Second, the authors add to all theories that regard novel technologies as a recombination of existing technologies in presenting word combinations from textual data as a suitable instrument for revealing recombination in patents. And third, the approach can be used by scholars as a complementary or even integrative tool with conventional forecasting methods like the Delphi technique or Scenario planning.

At least three practical implications arise from the study. First, incumbent firms of a technology branch can use this approach as an early-warning system to identify technological change and to identify opportunities related to their company’s technological competence and provide inspiration for new ideas. Second, companies seeking to tap into new markets may also be interested in the approach as managers could anticipate whether their company’s technological competences are in line with upcoming trends. Third, the approach may be used as a supportive tool for various purposes, such as investment decisions or technology life cycle analysis.

The approach introduces textual patent data as suitable means for forecasting activities. As the statistical validation reveals, the promising patents identified by the approach are cited significantly more often than patents with less promising prospects.