create an effective and standard predictive model to treat Alzheimer’s disease.

Literature Review

This article has used Predictive Modelling of the Progression of Alzheimer’s Disease with Recurrent Neural Networks (RNN) to identify the appropriate time for the patient regarding his/her next visit for medical checkup. This model has the capability to collect the various visits of a patient with different time intervals to predict new medical visit dates with a more even time interval. The study also discussed that more than 5.4 million people in the United States are living with Alzheimer’s which cannot be fully treated or reversed with the current medical and treatment system, however, with effective prevention technology its prevalence can be controlled. Various preventive or predictive models has been developed in the past however, almost all of them had a number of issues which made them less attractive. The use of this model helped in getting 99% accuracy based on the medical history of the patient (Wang, Qiu & Yu, 2018). In the study conducted by Wang, Qiu & Yu (2018) an RNN with LSTM cells-based progression model was proposed to predict the future stages of the Alzheimer’s disease. The model is found successful and authors showed their interest to use this model for the prediction of other chronic disorders.

Over the last five years, the research in the area of dementia risk prediction and specially for the Alzheimer’s disease got a boost. Numerous old models have been improved while some new models were also developed to increase prevention of this disease by predicting its numerous stages. In 2010, a systematic review identified that there are more than 50 models developed for the prediction of dementia and these models exhibited a difference in terms of risk score calculation, model accuracy level, follow up time, and disease outcome. This study identified a novel and effective linear model which is invented to predict the disease status in a future perspective. To check the effectiveness of their model, the authors used available data on Alzheimer’s disease. This study also addressed the issue of data missing through matrix factorization (Nie et al., 2017). This study has analyzed various articles in order to find that whether there is any model that could perfectly make the prediction regarding dementia. By analyzing various articles, this article contributed in this field by providing information about various studies and models that has been used for the prediction of dementia and Alzheimer’s disease. Although, there are various models developed by many researchers, however, still there is no such model about which it can be said that it is a perfect model for dementia/Alzheimer’s risk prediction among people due to the absence of risk score validation researches. There is a need to have lots of work to improve the existing models as well as to develop new models considering the weaknesses of existing models (Tang et al., 2015).

This study has investigated the relationship between Alzheimer’s disease and aging. Researchers has found a strong connection between aging population and Alzheimer’s disease and it is assumed that innovation could help in the partial resolution of the aging related societal problems. This study has contributed in this field by identifying a biomedical model of Alzheimer’s disease to reduce the social-culture aspects of the aging and Alzheimer’s disease. This model proposed a cure to Alzheimer’s disease; however, this model was abandoned due to the emergence of care models in 1990s and onward. The majority of models were discovered to make an early diagnostic of Alzheimer’s disease, however, due to the lack of any proper treatment the early diagnostics of this disease were remained useless as no cure was offered. The only way with which the early diagnostic or predictive technologies could help in the treatment of Alzheimer’s disease is that these early diagnostic models should eb a part of Alzheimer’s disease management in its early stages. This study ahs also discussed various aspects of human life as well as the use of technologies such as MRI, CT scan and chemical testing to predict the early diagnosis of Alzheimer’s disease, however, still there is a need for developing new models due to flaws in existing models (Cuijpers & van Lente, 2015). Alzheimer’s disease is accountable for 70% of the dementia cases across the world therefore, the therapeutic paradigm of this disease has been moved to secondary prevention. Various social implications and ethical concerns has been identified in preclinical predictive approaches, therefore, there is a need of a proper predictive modeling is required to address the challenges brought be prevention approaches. The majority of predictive models have raised some social implications and ethical concerns that the majority of the studies on this matter has overlooked. The predictive models like Statistical algorithms method or the methods of source data such as imaging data, family data, genetic data, cerebrospinal fluid examination, neurocognitive assessment, electronic/medical health record, demographics and family history have raised some sort of ethical and social concerns (Angehrn et al., 2019). This study has investigated the direction of the therapeutic paradigm with respect to Alzheimer’s disease. It is also concluded by the study that there is a need to identify predictive models that could predict the occurrence of this disease years before. This is the first study in this field which has paid attention to the social and ethical concerns raised by the technological development for the prediction of Alzheimer’s disease.

The study of Tang et al. (2015) investigated 1,234 articles to investigate the new developments in risk prediction of dementia and Alzheimer’s disease and concluded that new developments like non-APOE genes testing, incorporation of diet, application of non-traditional risk factor of dementia, ethnicity and physical function, and inclusion of some development in subgroups with diabetic individuals and those with different educational levels. However, after making an investigation of various studies, it is concluded that there is no single study that could be used for the prediction of dementia. Moreover, it seems impossible to have a predictive model that fits all. There is a high need to make researches for the development of existing predictive models as well as for developing new models, however, it is important to consider various predictive models (Tang et al., 2015).

According to the study of Haas et al. (2016) many predictive models for Alzheimer’s disease have failed due to the absence of reliable models. This is because the majority of models are computerized and there is a need for a more humanized kind of models that best suits the clinical situation. The biggest need is to make sure that data is shared among all the healthcare organizations because it allows researchers to address the various scientific questions in different predictive models. The availability of data will also enable the researchers to access both real life data and clinical trials data to innovate a more accurate and ethically sound predictive model. The diagnosis and prediction of Alzheimer’s disease is very difficult because of its different symptoms in different patients. The study of Haas et al. (2016) contributed in this field by identifying the various weaknesses of the existing predictive models. The presence of an effective predictive model could change the entire direction of the treatment of Alzheimer’s disease. The article has identified few real-world examples of such predictive models which contributed effectively in various CNS (central nervous system) diseases. Also, it is suggested that for the development of a predictive model, government and private organizations should make a partnership. Moreover, the progression of this disease from preclinical, mild and severe is different among different individuals. Instead on investigating appropriate predictive models, there is a need to invest in the training of physicians to make them ready and competent enough to manage Alzheimer’s disease at various stages. The improvement in the understanding level of the physicians could improve the overall cycle of treatment and management of the Alzheimer’s disease (Margolis, 2017). This study has identified a more realistic side of the Alzheimer’s disease that instead of developing a new predictive model, it is better to invest in the training of physicians and medical staff to deal with different types of patients at different stages of Alzheimer’s.

Due to the lack of discovery of the pathogeneses of Alzheimer’s disease there is no proper cure available for it to date. Since it is widely believing that pathogenic changes began to occur years before therefore, it is important to have an accurate and effective predictive model to accurately screen, diagnose and prevent this disorder. Unfortunately, due to the polygenic nature of Alzheimer’s disease, it has not been possible to effectively predict the level of Alzheimer’s disease (Nazarian & Kulminski, 2018). This study has stressed on the importance of discovering the biological process involved in Alzheimer’s disease because the Alzheimer’s disease pathogenesis in not fully discovered due to which not predictive model is working effectively. Once the pathological changes are fully discovered, it would become possible to develop an effective and standard predictive model to treat Alzheimer’s disease.

References

Angehrn, Z., Nordon, C., Turner, A., Gove, D., Karcher, H., & Keenan, A. et al. (2019). Ethical and social implications of using predictive modeling for Alzheimer’s disease prevention: a systematic literature review protocol. BMJ Open, 9(3), e026468. doi: 10.1136/bmjopen-2018-026468

Cuijpers, Y., & van Lente, H. (2015). Early diagnostics and Alzheimer’s disease: Beyond ‘cure’ and ‘care’. Technological Forecasting and Social Change, 93, 54-67. doi: 10.1016/j.techfore.2014.03.006

Haas, M., Stephenson, D., Romero, K., Gordon, M., Zach, N., & Geerts, H. (2016). Big data to smart data in Alzheimer’s disease: Real-world examples of advanced modeling and simulation. Alzheimer’s & Dementia, 12(9), 1022-1030. doi: 10.1016/j.jalz.2016.05.005

Margolis, R. (2017). Exploring Outcomes and Value across the Spectrum of Alzheimer’s Disease. Presentation, 1201 Pennsylvania Avenue NW, Washington, DC 20004.

Nazarian, A., & Kulminski, A. (2018). POLYGENIC PREDICTIVE MODELS FOR ALZHEIMER’S DISEASE. Innovation in Aging, 2(suppl_1), 102-102. doi: 10.1093/geroni/igy023.382

Nie, L., Zhang, L., Meng, L., Song, X., Chang, X., & Li, X. (2017). Modeling Disease Progression via Multisource Multitask Learners: A Case Study with Alzheimer’s Disease. IEEE Transactions on Neural Networks and Learning Systems, 28(7), 1508-1519. doi: 10.1109/tnnls.2016.2520964

Stallard, E., Kinosian, B., & Stern, Y. (2017). Personalized predictive modeling for patients with Alzheimer’s disease using an extension of Sullivan’s life table model. Alzheimer’s Research & Therapy, 9(1). doi: 10.1186/s13195-017-0302-6

Tang, E., Harrison, S., Errington, L., Gordon, M., Visser, P., & Novak, G. et al. (2015). Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review. PLOS ONE, 10(9), e0136181. doi: 10.1371/journal.pone.0136181

Wang, T., Qiu, R., & Yu, M. (2018). Predictive Modeling of the Progression of Alzheimer’s Disease with Recurrent Neural Networks. Scientific Reports, 8(1). doi: 10.1038/s41598-018-27337-w

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Predictive Modeling as a Preventive Technology in the Health industry

Running head: Predictive modeling 1

Predictive modeling 7

Predictive Modeling as a Preventive Technology in the Health industry
Topic area

The average human lifespan is increasing along with the world population, which poses new challenges to today’s treatment delivery methods. The health sector is capable of collecting massive amounts of data and look for best strategies to use the numbers. With the use of predictive modeling, the health sector has the potential to reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life.

Advances in predictive modeling as a preventive technology in the health sector should be designed to help clinically integrated networks manage large, complex patient populations. One of the challenges facing providers today is that predictive modeling requires a strong data infrastructure, user engagement, staffing and other resources.

Preventive technology could help make diagnoses more accurate and treatment regimens more precise, reduce labor costs, capture data faster, sort through vast amounts of data to gain insights needed to drive better care decisions and outcomes. With the use of predictive modeling and preventive technology, from a patient-facing perspective, they could improve health literacy. These instruments combined with patient-contributed data could also help predict and fill patients’ clinical knowledge gaps. In that way, patients could more confidently manage their own health and make healthier choices on their own.

For example, the use of the fit bit arm/wrist band could be extended into an integrated system that could collect patients’ health data continuously and send this data to the cloud which will allow doctors to monitor and compare this data and react every time if the results will be disturbing. If a patient’s blood pressure increases alarmingly, the system will send an alert to the doctor who will then take action to reach the patient and administer measures to lower the pressure.

Research question

What impact does predictive modelling on creating successful treatment plan for patients with diagnosis of Alzheimer’s disease?

Alzheimer’s disease is one mental problem that mostly affects the elderly population. This disease is characterized by a progressive memory loss leading to impaired cognitive functions. The condition is usually chronic hence affect the patient for a long time. Patients with, therefore, disease have a reduced quality of life coupled with continuous treatments. Use of predictive modeling technology in the management of this patient can play a significant role in creating a successful treatment plan for the condition. Predictive modeling technology has several benefits for both the patient and the provider of healthcare.

Predictive analysis or modeling in healthcare improves the accuracy of diagnosis. For patients with Alzheimer’s disease, using the predictive modeling technology help the primary care physicians to make an accurate diagnosis of the bug regarding the staging and presence of other comorbid condition such as dementia. To achieve this, the clinicians use the predictive algorithm provided by this model to assess for the stage of the disease and the presence of other conditions (Wang, Kung, & Byrd, 2018). As a result, the patient is usually screened using this model before being discharged home to promote patient safety and quality of life.

Predictive modeling technology play a significant role in preventive disease medicine and public health. In this case, this analytic technology helps care providers to prevent diseases and their complications from advancing by identifying populations at risk (Ritchie et al., 2015). Alzheimer’s disease patients are at risk of developing other mental condition such as dementia or promoting to the severely chronic stage that will acutely reduce the health status and life of patients. Therefore, primary care physicians use this model to screen the Alzheimer’s disease patients under their care for possible complications or deterioration. Knowledge gained about the disease using this analytic model is therefore used to implement safety precautions such as lifestyle changes that promote disease recovery. The model, thus, transforms the care of Alzheimer’s disease from curative to preventive since prevention is better than cure (Wang, Kung, & Byrd, 2018).

Predictive modeling technology in mental health provides physicians and psychiatrists with information on how to provide care for the individual patient. For a patient with Alzheimer’s disease that was diagnosed with the algorithm as per this model, the exact treatment methods required are also identified. This is different from the usual plan of care that is drawn from standard symptoms and treatment. The patient will be given specific drugs to meet their health needs. Also due to predictive analysis on the type of effective medications, the hospital can use this information to purchase only the required drugs from the pharmaceutical stores to prevent wastage and shortages of medicines (Bhagwat et al., 2018). Therefore, medication for Alzheimer’s disease will be readily available for use.

Predictive modeling in healthcare also has a direct impact on patients with Alzheimer’s disease. The use of the algorithm in diagnosis and prescription of treatment results in patients getting the drugs that are only effective or active against their condition. Use of specific medications to treat this condition increases patient knowledge on how to promote the effectiveness of these medications (Bhagwat et al., 2018). Patients will be aware of potential complications and learn how to prevent such from occurring. This is, in turn, support evidence-based practice where patient-centered care is practiced. As a result, quality and safe care is practice hence promoting better health outcomes for the patients.

The significance of the study

The purpose of healthcare predictive modeling is to help doctors make data-driven decisions within seconds to improve a patients’ treatment. By using data-driven findings to predict and solve a problem before it is too late, also assess methods and treatments faster, keep better track of inventory, involve patients more in their own health and give them the tools to do so.

This is very useful with patients who have a complex medical history and suffering from multiple conditions. This tool would be able to predict, for example, who is at risk of diabetes, and thereby be advised to make use of additional screenings or weight management. For year’s gathering huge amounts of data for medical use was costly and time-consuming. With technology improving on a daily basis, it is easier to not only collect such data but also to convert it into a useable form to provide better care.

Healthcare providers had no direct incentive to share patient information with one another, which made it harder to utilize the power of predictive modeling and preventive technology. Now that more of the health sector are getting paid based on patient outcomes, they have a financial incentive to share data that can be used to improve the lives of patients while cutting costs for insurance companies. Healthcare needs to catch up with other industries that have moved from the standard regression-based methods to a more future oriented like predictive model, to improve patient outcomes while reducing spending.

References

Bhagwat, N., Viviano, J. D., Voineskos, A. N., Chakravarty, M. M., & Alzheimer’s Disease Neuroimaging Initiative. (2018). Modeling and prediction of clinical symptom trajectories in Alzheimer’s disease using longitudinal data. PLoS computational biology, 14(9), e1006376.

Breuker, D., Matzner, M., Delfmann, P., & Becker, J. (2016). Comprehensible Predictive Models for Business Processes. MIS Quarterly, 40(4), 1009-1034.

Ritchie, C. W., Molinuevo, J. L., Truyen, L., Satlin, A., Van der Geyten, S., & Lovestone, S. (2016). Development of interventions for the secondary prevention of Alzheimer’s dementia: the European Prevention of Alzheimer’s Dementia (EPAD) project. The Lancet Psychiatry, 3(2), 179-186.

Wagenen, J. (2017, November). Predicting-analytics-3-Big-Data Trends in Healthcare. Healthtech, pp-1-6. Retrieved from https://healthtechmagazine.net/article/2017/11/predicting-analytics-3-big-data-trends-healthcare.

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and

potential benefits for healthcare organizations. Technological Forecasting and Social

Change, 126, 3-13.

Zheng, B., Zhang, J., Yoon, S. W., Lam, S. S., Khasawneh, M., & Poranki, S. (2015). Predictive modeling of hospital readmissions using metaheuristics and data mining. Expert Systems with Applications, 42(20), 7110-7120.

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Week four Discussion

https://www.npr.org/sections/health-shots/2019/02/25/697052006/anger-can-be-contagious-heres-how-to-stop-the-spread

please see attachments with instruction

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The internal dynamics of firms: The throughput component

A theoretical framework of organizational change

Jacobs, Gabriele ; Arjen van Witteloostuijn ; Christe-Zeyse, Jochen . Journal of Organizational Change Management ; Bradford Vol. 26, Iss. 5, (2013): 772-792. DOI:10.1108/JOCM-09-2012-0137

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Purpose – Organizational change is a risky endeavour. Most change initiatives fall short on their goals and produce high opportunity and process costs, which at times outweigh the content benefits of organizational change. This paper seeks to develop a framework, offering a theoretical toolbox to analyze context-dependent barriers and enablers of organizational change. Starting from an organizational identity perspective, it aims to link contingency-based approaches, such as environmental scan, SWOT and stakeholder analysis, with insights from organizational behaviour research, such as knowledge sharing and leadership. Design/methodology/approach – The framework is informed by long-lasting field research into organizational change in an international policing environment. The theories in the framework are selected from the perspective of field validity in two ways; they were chosen because the topics covered by these theories emerged as relevant during the field research and therefore it can be expected they have applicability to the field. The authors’ insights and suggestions are summarised in 13 propositions throughout the text. Findings – The analysis provides a clear warning that organizational change is more risky and multifaceted than change initiators typically assume. It is stressed that the external environment and the internal dynamics of organizations co-determine the meaning of managerial practices. This implies that cure-all recipes to organizational change are bound to fail. Originality/value – This paper makes an ambitious attempt to cross disciplinary boundaries in the field of organizational change research to contribute to a more comprehensive and holistic understanding of change processes by integrating perspectives that focus on the internal context and the external environment of organizations.

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Organizational change as a risky strategy

Organizational change is omnipresent, being the raison d’être of the consultancy industry ([71] Sorge and van Witteloostuijn, 2004). Modern organization sciences have produced a large amount of insights into a wide variety of issues related to organizational change. And of course, consultancies successfully launch new organizational change “products” all the time. However, organizational change is still often associated with failure. A case in point is the persistently high number of merger and acquisition deals that fail in the post-integration stage (totalling approximately 70 per cent) or the (circa) 30 per cent that fail before consummation (see, e.g. [19] Dikova et al. , 2010; [54] Muehlfeld et al. , 2012; [11] Brakman et al. , 2013). Most organizational change projects, of course, deal with less impactful issues than mergers and acquisitions, where negative effects may be expected to be less threatening to organizational survival than M&A deals gone awry. Yet, change projects with a smaller scope are also prone to poor planning, disappointing results and unintended consequences that divert resources from operational tasks, disrupt well-established routines, and shatter the trust of employees and business partners alike.

Organizational change theories need to negotiate two hurdles: scholarly quality and practical relevance ([60] Pettigrew et al. , 2001). Key questions in research on organizational change are: Why do so many organizational change initiatives fail to deliver? And how can organizational change processes be implemented in a way that assures success? Organizational change is a notoriously complex phenomenon; it is only natural that research on organizational change addressed this complexity from numerous more or less complementary or contradictory, but equally legitimate perspectives. These perspectives stretch across disciplinary boundaries, across methodological camps, and often across contradictory visions of organizations. The result is a debilitating fragmentation of theories of organizational change, with widely different perspectives – sometimes complementary, but sometimes contradictory – blossom side by side in the large organizational change literature. One angle to illustrate this state of fragmentation is that of the level of aggregation: micro (individuals) and, meso (groups and organizations) and macro (organizational environment and populations of organizations).

The fragmented nature of the field of organizational change research

Some research focuses on a micro perspective, analyses the psychological aspects of organizational change, focusing on what organizational change does to human beings – typically to change recipients. Examples involve attitudes to change in general ([73] Vakola and Nikolaou, 2005), perceptions of change ([80] Weber and Weber, 2001), strategies coping with uncertainty ([20] DiFonzo and Bordia, 1998), and organizational change induced stress.

Another research tradition takes the meso perspective. This perspective addresses issues relating to the organizational context of organizational change, as well as how organizational change affects and is affected by organizational identification and institutionalisation processes. Examples are research on group processes and social identities ([48] van Leeuwen et al. , 2003), and Selznick’s seminal book Leadership in Administration . In this line of research, organization-level taken-for-granted values and default expectations play critical explanatory roles.

A third line of research looks at organizational change from a macro perspective, adopting the lens of sociology’s organizational ecology to study structural reproducibility and organizational inertia, the effects of (early) imprinting and organizational change on the organization’s fitness and competitiveness, and ultimately on the mortality hazard of organizations. The primary focus is on how these issues work out in populations of similar organizations. [36] Hannan and Freeman (1984), [33] Hannan et al. (2004) or [34] Hannan and Baron (2002) illustrate this research tradition.

Another angle that reveals the state of fragmentation of the organizational change literature is that of disciplines, as already hinted at previously. The academic disciplines that are typically called on include (but are not at all restricted to) social psychology, sociology and economics. From a more applied perspective, the rich literature on organizational change is typically scattered across organizational behaviour ([56] Oreg et al. , 2011) and strategic perspectives on organizational change ([67] Schwarz and Huber, 2008). These different disciplines adopt a rather narrow focus, concentrating on the workplace and individual aspects of organizations, on the one hand ([37] Herscovitch and Meyer, 2002; [41] Jacobs et al. , 2008), and the performance-survival aspects of organizations, on the other hand ([7] Barney, 1991; [21] Donaldson, 2001; [55] North, 1990). Since these disciplines themselves are subdivided into many different schools of thought, it is understandable that the “theories” of organizational change offered in these disciplines are fragmented to the extreme.

Even though the field developed clear and useful distinctions, such as the separation of content and process effects of organizational change ([6] Barnett and Carroll, 1995), this welcome clarity resulted in further fragmentation of theories, since the strategy literature primarily focuses on the (allegedly) beneficial, and highly organization and environment-specific content effects, and emphasises the need for flexibility and adaptability, while others are interested in the predominantly negative, and not organization-specific, process effects, assuming that the content effect of the change are, at best, randomly positive or negative.

There is little consensus on how to evaluate organizational change processes: Is it appropriate to focus mainly on perceptions of change recipients, like psychological research does ([56] Oreg et al. , 2011)? Should one, like [36] Hannan and Freeman (1984), pay attention to the overall wellbeing, fitness or more precisely mortality hazard of the organization and see how change in general influences these? Or should one primarily be concerned with the effects of change on the talent pool of the organization, such as in [8] Baron et al. (2001)? Would it be more appropriate to look at the speed of the implementation of the change, since the speed drives the opportunity costs of the organizational change, or will a focus on the relationship between change in the employment blueprints and the economic outcomes, such as growth or the time between founding and the initial public offering as in [34] Hannan and Baron (2002), generate more valuable insights?

Many of these studies yielded valuable insights, and the value of these insights is responsible for the temptation researchers are exposed to: Borrow from these theory fragments in order to generate novel explanations and derive valuable predictions. But it is not difficult to see that borrowing from separate theory fragments carries certain risks: The theory fragments briefly described previously are not always consistent with one another, and the complex explanations built on the insights they generate might lack coherence. The current paper attempts to carve out the set of insights that can be fruitfully combined with each other in a consistent manner so that they offer a logical basis for the propositions offered. In so doing, we illustrate how we can enter new ground by integrating arguments from different theory fragments in a way not done before, crossing disciplinary boundaries and developing a multi-level logic. Specifically, in this paper, we advocate an integration of organizational behaviour and strategic approaches to develop a single organizational change theory.

Towards an integrated organizational change theory

We aim at enlarging our understanding of organizational change, by looking simultaneously through the individual-focused micro lens and the organization-oriented macro lens. Our framework explicitly relates to both the inside and the outside world of organizations, which makes the case for an interdisciplinary and multi-level approach to the study (and practice) of organizational change. In so doing, we link insights from micro-level theories of individual change acceptance to macro-level perspectives on the environment, with input from meso-level theories on leadership and organizational identity, implying that we bridge organizational change theories from psychological, sociological and economic perspectives. We are aware that we can in no way fully live up to our ambitious attempt, and that we need to select some limited theoretical insights from these different disciplines.

Our selection is, next to theoretical considerations, guided by an emergent understanding during our field research, where we identified theories addressing issues raised by practitioners in the field of organizational change. Our unified theory of organizational change is informed by three main observations of the nature of organizational change. First, organizational change is a risky strategy, as it is often related to the violation of an organization’s core cultural values and, potentially, the organization’s identity ([35] Hannan et al. , 2007). Therefore, we explicitly focus on the vital role of organizational identity to explain the successes and failures of organizational change. Second, the analysis of organizational change needs an approach that can account for the specifics of the organization in question. Yet, the organizational change industry is dominated by consultancies that offer universal solutions to organization-specific problems ([71] Sorge and van Witteloostuijn, 2004). Scholars have noted that this tendency to rely on universal remedies is counterproductive ([57] Ostrom, 2007). Therefore we incorporate a contingency perspective in our framework of organizational change, suggesting that it is important to identify the external and internal conditions needed to ensure the success of specific organizational change programmes in specific organizations and contexts.

Third, there is still a widespread habit within organizational change research to ignore the major influence of cross-country cultural and institutional differences. This is closely related to our second observation, and it has also been substantiated in organization theory and practice ([70] Sorge, 2005). It boils down to the fact that what works in one organization, culture, or country, may well produce failure in another organization, culture, or country. Or, more subtly, practices that look similar across organizations, cultures, or countries on the surface often turn out to be very different if analysed more carefully. As [60] Pettigrew et al. (2001) note, in a culturally diverse world, scholars of organizational change cannot continue to assume with a quiet heart, that the change patterns in their corner of the world reflect those experienced on a wider, global stage.

This does not imply that the overall logic of the theory we propose here is idiosyncratic, being tailored to each and every specific case – it is not. Rather, we believe that our framework is general, although the details of how things work out in practice are specific to the context. Even though two organizations might appear to be alike to analysts, they might have different audiences and, as a consequence, their identities might be very different. Such differences have important implications for the types of organizational change processes that are adopted, as well as the acceptance or resistance of specific change projects in different organizational contexts and among different parties. To bring to life our theoretical arguments, we decided to add propositions and examples. First, we formulate a series of 13 propositions that provide examples of core theoretical insights or insights that we believe are interesting to explore further in future work. This list of 13 propositions is by no means exhaustive, but we hope that it clarifies the kind of follow-up work we envision. Second, to put some real-world flesh to our theoretical argumentation, we illustrate our arguments with examples from police organization in a series of quotes. We do so because our theoretical framework is currently applied in the context of a large EU project on organizational change in police forces in ten European countries. In this paper’s discussion, we will introduce this project in a little more detail and illustrate how we put our theoretical framework into research practice.

Theoretical framework

Our macro-lens brings a fundamental observation to the theoretical discussion that is often ignored by micro-level researchers: Organizational change does not emerge and evolve in splendid isolation. Stakeholders inside and outside of the organization tend to be heavily involved before, during and after the change process ([25] Frooman, 1999). Our micro-lens, in turn, draws attention to the role of organizational members in organizational change, an aspect that is often overlooked by macro-level scholars of strategic management. We embed our analysis of internal organizational change processes in a larger cultural and institutional framework, focusing on differences across societies. To organize the arguments, we frame this process in a simple input-throughput-output model, as introduced in Figure 1 [Figure omitted. See Article Image.].

Input relates to the antecedents of change (the period before the change), throughput to the process of change (during), and output to the consequences of change (after). The glue that binds all of these elements of our theoretical framework together is organizational identity and how this may be affected by organizational change. Therefore, before introducing our unified input-throughput-output framework, we first discuss this essential nexus between organizational identity and organizational change.

The effects of organizational change on organizational identity

Following [1] Albert and Whetten (1985), the organizational structure and the organizational culture, or architectural and cultural codes ([35] Hannan et al. , 2007), provide the answer to the basic question of (internal) organizational identity: “who are we as an organization?” These central, enduring and distinctive elements of an organization constitute the requirements for a shared belief structure, a set of more or less consensual expectations about “how an organization such as ours should behave in a situation like this” that makes consistent and coherent organizational action possible ([41] Jacobs et al. , 2008; [78] Van Rekom and Whetten, 2007).

Shared expectations can successfully influence, sometimes even orient, organizational action, because the formal procedures are typically incomplete and partial, and they cannot deal with all possible contingencies. So, answers to the question “What should we do in a situation like this?” are often derived from the common understanding of who we are as an organization, and default rules on “how an organization like ours should behave in a situation like this.” Taken-for-granted behavioural patterns, reflecting the distinction between expected and unexpected acceptable and non-acceptable behaviour, are key components of organizational identities ([62] Ravasi and Schultz, 2006).

Some organizational changes are well aligned with the organizational identity, and do not go beyond a formalisation and refinement of already existing but not yet formalized practice. Others, however, are partially in conflict with organizational identities, while still others, are or can be experienced as fundamental challenges to valued organizational identities ([26] Gioia et al. , 2000; [77] Van Knippenberg et al. , 2002; [64] Rousseau, 1998).

To the extent that individuals identify with their employing organization, the organizational identity reflects on how people see themselves – organizational membership and organizational identity are merged with the employees’ sense of self ([4] Ashforth and Mael, 1989; [27] Glynn, 2000; [74] Van Knippenberg, 2000). Changes to the organization’s identity are therefore often experienced as threats to members’ individual identities ([22] Dutton et al. , 1994; [23] Fiol, 2002; [41] Jacobs et al. , 2008).

When internal audiences such as groups of employees observe that the taken-for-granted expectations concerning an organization are not complied with, they often reduce their identification and loyalty to the organization. Hannan et al. refer to this as assigning lower grades of membership to the organization. Consequently, this internal audience will find offers of the organization intrinsically less appealing, contributing to HRM problems like sick leave and the potential inability of the organization to mobilize additional human resources. People value a sense of continuity of identity ([62] Ravasi and Schultz, 2006) – a sense that across past, present and projected future they essentially are the same person or collective (i.e. organization) – and therefore often strongly resist organizational changes affecting this sense of continuity. Thus, a key challenge for change process leaders is to act, not only as change agents, but also as agents of continuity – a challenging balancing act indeed ([76] Van Knippenberg et al. , 2008).

Organizational identity not only matters for internal audiences such as employees, but also for external audiences. If stakeholders perceive code violations and if they recognise that their expectations are not met, the organization may lose legitimacy in the eyes of key external audiences. This can have serious consequences as some stakeholders may control vital resources. In the case of police forces, politicians may reduce their political support if the police fail to perform according to the expectations of the public, or the media may undermine public trust in the police by focussing on perceived failures or violations in standards.

A quite significant change process in many European police forces was connected to the implementation of management methods from the private sector into police organizations. In times of severe budget restrictions and in times of frequent criticism of supposedly slow and inefficient bureaucratic procedures, pressure grew in some European countries to increase efficiency in police forces by introducing performance measurement and cost accounting systems, management by objectives, benchmarking and other instruments derived from the private sector. Many police officers, however, felt alienated by the attitude of some politicians and consultants that apparently did not seem to distinguish between a police force and a private company. Their identity as police officers implied serving the common good and fighting for security and justice. Being subjected to questions of efficiency was considered by many as an unjustified and inappropriate equalization of the police with a private sector that was, in their eyes, primarily interested in selling goods and making profits ([14] Christe-Zeyse, 2007a).

The need for a cross-national comparison of organizational change

We aim at developing a general theory, applicable to all kinds of organizations in all types of environments. The precise nature of the role of organizational identity can only be seen if we can control for the impacts of other cultural differences, such as those deriving from nationality, geography, ethnicity or religion ([60] Pettigrew et al. , 2001). More specifically, these local cultures, in combination with the history of these types of organizations in different countries or regions, establish interpretative frames that are used to disambiguate and complete the otherwise partial procedures and regulations of organizations – that is, so to speak, to fill the inevitable gaps in the organizational structure by imposing informal cultural codes.

Cultural difference can refer to something as “soft” as the tone in which an order is given. In some police forces, an order is understood to be something that does not allow for any kind of debate, interpretation, or disambiguity, whereas in other police forces an order can also be understood as a consensual decision after a cooperative and reciprocal process of deliberation and advice.

It is important to recognize that although the same organizational categories, forms or types (with respect to police appraisal and promotion systems, ranks, arms, uniforms, the right to search and arrest, etc.) may be available in all countries, which should provide a good basis for common organizational identities, daily organizational life comes with different interpretative schemata to make sense of codes, practices, procedures and values ([70] Sorge, 2005; [49] Magala, 2009). Thus, a seemingly universal template tends to be moulded into local practices, producing idiosyncrasies in the process.

A case in point is the way police officers approach citizens. It makes quite a difference whether a police officer acts in the role of a service provider or as the armed representative of the executive power. The setting may seem similar: A police officer stops a car and asks the driver for his or her driver’s licence and registration. But depending on traditions, cultural norms, self-perceptions, legal requirements etc. the situation may in fact be very different, ranging from a friendly chat to a rather aggressive looking demonstration of dominance and submission ([51] Martin, 1999).

What holds true when comparing organizations from different cultural settings with each other also holds true when looking at the relationship between an organization and other actors from the same cultural setting. Each audience within the organization (i.e. different departments or specialized units), but also outside the organization (i.e. the public, the ministry, the prosecutor) has a different cultural interpretation of expectations or relationships. Ambiguous procedures and regulations are interpreted in numerous different ways and different parties develop different responses in relation to procedural ambiguities. In this sense, idiosyncrasies develop in each specific work relationship and (organizational, national) culture provides a general setting by providing a lens for sensemaking ([49] Magala, 2009; [81] Weick, 1995).

All European police forces have explicit anti-corruption rules, but when it comes to very specific situations in which officers interact with citizens, these rules are sometimes not as unambiguous as they might seem. Being helpful and friendly, exchanging information and returning favours might be part of a cultural tradition in one context and a case of corruption in another. What is acceptable and what is not, may not be entirely determined by formal rules or cultural traditions, but very often needs to be disambiguated with respect to individual audiences and specific situations ([61] Punch, 2000.)

Next to (organizational and national) culture, we explicitly integrate into our framework the more tangible aspects of the environment, which are often ignored in the literature on organizational change (see also Bayerl et al. , in this issue), but are nevertheless of high importance. The direct environment of actors influences their sensemaking (i.e. ecological sensemaking; [82] Whiteman and Cooper, 2012) and frames the meaning they give to practices, technologies and forms. Hard facts such as budget cuts, legal constraints, or political instability co-determine organizational identities and are therefore included in our framework of organizational change. This implies that we have to integrate insights from “hard” contingency and strategy theories into our “soft” identity-based theory of organizational change. This is precisely what we do in our unified input-throughput-output framework of organizational change, to which we turn now.

A unified framework of organizational change

Figure 1 [Figure omitted. See Article Image.] summarises our theoretical logic in the context of a simple input-throughput-output framework. The framework’s theoretical lens cements these theory fragments together in an overarching framework, illustrating that organizational change may only be understood by systematically analyzing all constitutive elements and the way they interact. In what follows, we will explain these elements of our unified framework of organizational change.

Triggers of change: the input component

We start with the input component of our framework. As is known from a large contingency literature in the organization sciences ([47] Lawrence and Lorsch, 1967; [58] Parker and van Witteloostuijn, 2010), fit is a key driver of organizational performance. Fit is defined as the alignment of an organization’s internal features with that of its external environment, to enhance performance ([52] Miles and Snow, 1994). [30] Hannan (1998) suggested that, at their founding, organizations are typically aligned with their environment, but as they age, the alignment weakens, requiring serious effort to keep pace with a changing environment. If an organization experiences a misfit, which comes with inferior performance, organizational change is needed to restore fit.

However, to be able to do so, the organization has to develop deep insights into both the environment of the future to which it needs to adapt, as well as into the current internal weaknesses that have to be changed into future internal strengths. This implies that the external antecedents of organizational change are related to the external opportunities and threats in the broader environment. Similarly, internal strengths and weaknesses of the organization can also trigger organizational change. So, the starting point of our unified theory of organizational change is an evaluation of external opportunities (O) and threats (T) in combination with internal strengths (S) and weaknesses (W), which is known as a SWOT analysis in the classic strategic management literature.

When the predominantly stable environment of Western European police in the 1950s and 1960s changed from stable to dynamic (student rebellion, value changes, anti-war protests, terrorism, etc.), police were increasingly under pressure to change the bureaucratic, centralized and mechanistic structures that used to fit so well with the stable environment of the past, into a more flexible and technology-driven structure that seemed to promise a better alignment with the challenges of the 1970s and 1980s. Around the turn of the century, new challenges arose. The end of the cold war, globalization, open borders, and new technologies (internet, social media, et cetera) made existing structures and arrangements seem too slow and bureaucratic to effectively deal with several diverging challenges at the same time. In particular, the police faced a growing need to comply with citizens’ concerns on a local basis, while at the same time dealing with the threats of terrorism, internet crime, organized and international crime on a national, supranational or even global level. Cross border cooperation between police forces, the implementation of new technologies as part of investigative work, international police missions in areas such as Kosovo or Afghanistan, and new surveillance technologies at airports, train stations and public locations may serve as an illustration of the attempts made to restore fit in response to such external changes and threats.

The relevance of the macro-environment for organizational change

The strategic management literature recommends the so-called PESTL approach as an organizing framework to monitor external opportunities and threats ([43] Johnson and Scholes, 2000; [44] Johnson et al. , 2005). This framework combines the analysis of political (P), economic (E), societal (S), technological (T) and legislative (L) issues. Each and every element of the PESTL framework is associated with subsets of tailor-made theories that may guide the environmental scan ([84] van Witteloostuijn, 1996). However, a SWOT analysis is only complete when accompanied by an analysis of the internal strengths and weaknesses. Central concepts in this internal analysis include organizational assets, capabilities, competencies and resources. Existing frameworks offer a series of four criteria to evaluate the strengths (or weaknesses, for that matter) of the key resources that make organizations tick ([7] Barney, 1991). Essentially, this implies an assets-capabilities-competencies-resources evaluation (ACCRE) of the efficiency and effectiveness of an organization’s resources, in light of the organization’s primary aims and objectives.

Next, the outcomes from the external PESTL and internal ACCRE analyses are brought together to assess the extent of perceived misfit. In so doing, the weaknesses and strengths of an organization are pitted against the opportunities and threats associated with its external environment. This exercise is at the heart of a modern contingency analysis ([58] Parker and van Witteloostuijn, 2010):

P1. A fit between the external environment and an organization implies that organizations are good at performing the tasks expected from them, that they effectively and efficiently react to the challenges of the outside world, and that they use their resources to the maximum effect. There is no need for organizational change.

P2. A misfit between the external environment and the organization means that organizations cannot appropriately react to the outside challenges and fail to fulfil the expectations of internal as well as external stakeholders – in short, that they are inefficient and ineffective. Organizational change is needed.

The result of such a fit analysis is a taxonomy of practices that succeed vis-à-vis those that fail, conditional on the nature of the environment and the type of organization. The aspect of conditionality is crucial: After all, it is rather unlikely that practices that promote efficiency and effectiveness in, say, a police station in Paris are equally valuable for the Romanian border police. Also we would like to note that the assessment of strengths and weaknesses is not straightforward or unambiguous. We need to consider from who the assessment of strength and weakness comes, and we should also evaluate whether this assessment matters for all audiences and under all (future) circumstances. A case in point is security procedures at airports. It might be only a minor goal of these procedures to make flights more secure, and their higher goal might be the perceived security by the public and the public perception that politicians take security issues seriously. In this sense, security procedures can be weak in terms of their technical effectiveness, but strong in the sense of their public effect, and vice versa .

Knowledge sharing and technology as triggers of organizational change

Organizational life is increasingly an information-rich and knowledge-intensive practice. Key to organizational learning – and hence to the design of a successful organizational change programme – is knowledge of which practices work well and which do not. Therefore, knowledge sharing between organizations is argued to be essential for organizational success, as is emphasised in the so-called knowledge-based view of the firm ([29] Grant, 1996).

Conceptually, knowledge sharing is the exchange between two or more parties of potentially valuable information (e.g. [18] Davenport, 1997; [39] Ipe, 2003), and involves both seeking and providing knowledge ([38] Ingram, 2002). Knowledge sharing generates competitive capabilities and contributes to sustained performance ([69] Slater and Narver, 1995). Organizational knowledge sharing is not a singular and isolated process, but an on-going interplay within and between organizations via people and technology ([10] Berg et al. , 2008). Specific knowledge-sharing practices are shaped by barriers and enablers at the individual, organizational and technological level, and are part of and contribute to the external and internal environment of organizations. Individual employees and organizations learn from best practices within their own organization, but also within their sector or even across sectors or on a global scale. Implementing such best practices leads in many cases to organizational change:

P3. Knowledge sharing within and between organizations triggers organizational change.

Scholars in the field of public management stress the relevance of knowledge sharing in the sense of cross-sector collaborations ([12] Bryson et al. , 2006). Applied to the police this means that police organizations need to exchange knowledge and practices with relevant stakeholders (i.e. municipalities, health services, government, but also organizations in the private sector) in order to adapt to increasingly complex demands. To ensure that such rich knowledge exchange is successful, skilful leaders are needed to integrate “people, processes, structures and resources” ([2] Ansell and Gash, 2008).

However, the importance of knowledge sharing as a critical factor in change processes goes beyond exchanging information on best practice or mistakes to be avoided. Successful inter-organizational knowledge sharing depends on the comparability of the organizations. Just transferring best practices from one organization to another could lead to a serious misfit of practices. Best practices need to be translated into the context of the respective (recipient) organization:

P4. Knowledge sharing is most likely to be successful when organizations share similar characteristics and operate within similar environments.

In addition to knowledge sharing, our model pays special attention to the role of technology in organizational change processes. Since the introduction of assembly lines, it has been widely acknowledged that technology functions as an agent of change in many respects, and must be handled as a key contingency factor. Technology can facilitate knowledge sharing, trigger new practices of work and influence methods of internal and external organizational communication, to name just a few functions. Most of the technology-related organizational change literature either focuses on the role of technology as such ([28] Gosain, 2004) or on the role of social dynamics within organizations ([46] Latour, 1996).

More recent debates on the role of technology in organizational change stress the importance of having technology embedded in organizations ([45] Labatut et al. , 2012; [79] Volkoff et al. , 2007) and of integrating material and social perspectives on technology. Especially in an international setting, it seems increasingly vital to understand how the environment and organizational features mediate the social meaning that is given to technology, and how this can trigger and shape organizational change processes:

P5. Technology implementation is a highly context contingent process that triggers organizational change differently depending on the organizational context.

In the late nineties, some police forces in Germany introduced a system to record work hours in a cost accounting system in order to get data on how to use tight resources more efficiently and shift resources from inefficient procedures to core activities of policing. After an initial phase of getting used to typing in the required data into the correct fields and after the usual complaints (“another useless statistical procedure”), police officers were expected to adopt the new software as one of the many unavoidable chores that shape a police officer’s life and ultimately become part of their daily routines. But despite sufficient information on why this change was necessary, a large number of police officers refused to get used to it, and resentment instead grew over the years. It soon became obvious that the new software was not just any kind of culturally “neutral” tool, but was considered part of a new management philosophy largely shaped by a model of private business that was resented on principal grounds. Data input was mostly inaccurate, supervisors didn’t use the data, because they couldn’t trust them, and after several years, some police forces quietly abandoned the plan to introduce cost accounting systems as the basis of a new management data base altogether ([15] Christe-Zeyse, 2007b).

The internal dynamics of organizations: The throughput component

Throughput processes take place within the organization. The wish to engage in organizational change may well be triggered by a perceived misfit, as defined previously. This may be externally driven, given new pressures from the environment, or internally triggered by organizational leaders who believe that internal weaknesses have to be repaired (or a combination of the two, for that matter). At this point of the argument, two remarks are worth making.

First, in practice, it is the subjective perception of (mis)fit that counts as an organizational change trigger, not the “objective” outcomes of a SWOT analysis. In the noisy circumstances of organizational life, mistakes are inevitable. Second, of course, perceived misfit in the sense of a misalignment in SWOT analysis is not the only motivation for organizational change. For instance, managerial power and control-restoring aims are cited as alternative organizational change drivers ([83] Wittek and van Witteloostuijn, 2013). Knowledge sharing and best practices observed in other organizations might lead to the start of change processes, just as the implementation of new technologies can lead to organizational change.

The literature on organizational change offers insights into the internal processes launched by such organizational change initiatives. Here, we would like to summarise these effects by focusing on the potential content benefits and the potential process losses of organizational change ([6] Barnett and Carroll, 1995). In principle, to boost organizational performance, the content of change should be such that weaknesses will be ameliorated or bypassed, and strengths will be reinforced or exploited. But some of these changes also produce losses that are unexpected and difficult to observe ([31], [32] Hannan et al. , 2003a, b; [24] Ford et al. , 2008).

A new training programme aimed at improving the social skills of community police officers is supposed to improve a police station’s fit with the societal demand for citizen oriented police work. However, such a change intervention may also come with unexpected process losses. For example, the social skills training programme may trigger resistance from officers strongly believing in the action-oriented crime fighter profile of police, vis-à-vis the more preventive and citizen oriented practices associated with the training programme. This, in turn, may trigger discussions about the perceived “softness” of the new course the police force has embarked on in general – discussions that may lead to perceptions of cognitive dissonance between the officers’ perceptions of good policing and the perceived objectives of leaders ([40] Jacobs et al. , 2007).

Frequently, perceptions such as the one described in the quote which follows, extend to areas that are not even related to the original trigger. In our case, police officers may find proof of the new “softness” in other areas as well, be it in the way a new leader communicates or the tone of a recent press release or a change in the web site design of their police force. It lies in the nature of such sensemaking processes that they cannot be determined by “above”.

[36] Hannan and Freeman (1984) argue that process losses are particularly large if the core of the organization, such as its work floor culture or set of objectives, is affected by the initial intervention – as this core defines the organization’s identity. Under such circumstances it is expected that process losses will be larger than content benefits. Hannan et al. argued that high-centrality changes (that is changes that touch on the core features of the organization) lead to longer cascades of change and by doing so increase the opportunity costs associated with the initial change. Organizational changes explicitly targeting core organizational features belong the most dangerous and demanding change endeavours:

P6. If organizational change only relates to peripheral features, which are less relevant for the organizational identity, the content benefits might well be larger than process losses and vice versa.

P7. Change that touches on the core of the organizational identity often weakens or even eliminates the potentially beneficial effects of this change.

A key moderator, or contingency, of the effect of organizational change processes is leadership ([63] Romme and van Witteloostuijn, 1999). It is extremely hard, if not outright impossible, for organizational change to be successful without the willing and proactive engagement of the organization’s employees. This commitment cannot be taken for granted, however – employee resistance to change has often been cited as a primary cause of change failure ([3] Argyris, 1990; [23] Fiol, 2002). Yet, scholars increasingly challenge traditional perceptions of change resistance, which cast employees as stubborn saboteurs of smart change endeavours. Resistance to change should rather be seen as a warning for ensuing counterproductive change effects or threats to the organizational identity ([24] Ford et al. , 2008):

P8. Resistance to change can function as a warning signal of organizational identity threat, with important implications for change outcomes.

Leadership plays a key role in building the legitimacy of and commitment to the change process ([9] Bass, 1985; [16] Conger and Kanungo, 1987; [68] Shamir et al. , 1993):

Change acceptance cannot be enforced by decree, but senior police officers accustomed to leading police staff under “normal” circumstances might not necessarily be well equipped to explain the need for change and the consequences that may accompany such actions. In order to facilitate acceptance of attempts to restructure police organizations, ministries of the interior in several European countries started to spend significant time and effort in designing communication strategies, setting up information and participation campaigns, offering training courses, and/or installing web-based information channels. A sizeable number of police forces, however, still rely on the assumption that a clearly worded order usually suffices to explain the need for change and thus overcome any potential resistance ([65] Santos and Santos, 2012).

Effective leadership anticipates the negative effect of an organizational change programme, whereas ineffective leadership fails to do so. Effective leadership will dampen the process losses, while ineffective leadership will make matters worse ([16] Conger and Kanungo, 1987). Leadership is, hence, directly connected to the issues of organizational change and identity. Organizational identity threats elicited by organizational change lie at the core of concerns regarding the legitimacy of change, also driving employee resistance, lack of involvement and weaker commitment to change processes (e.g. [76] Van Knippenberg et al. , 2008):

Neighbourhood policing in England was restructured quite dramatically around 2008 by extending some police powers to Special Constables and Police Community Support Officers in order to increase perceived security, let warranted police focus on higher levels of crime and improve the relationship between the police and the public. In addition to that, a “Policing Pledge” was issued, which was a ten-point commitment to the public and was signed up to by all 43 police forces in England and Wales in December 2008. It contained rather ambitious targets regarding the performance of police forces all over the country. The change was perceived by many police officers as a “seismic shift” affecting the role of police officers, their relationship with the community, their cooperation with external stakeholders and their day to day tasks. Many police officers who had for many years focused on fighting crime, dealing with suspects and victims, hadn’t “walked the beat” for decades and needed to readapt themselves to talk to “ordinary” citizens in order to improve their community presence. Leadership turned out to be a critical factor regarding the acceptance of this change, and an assessment by Her Majesty’s Inspectorate of Constabulary found that four out of every five police forces were falling short of the Policing Pledge promise. In July 2010, the new UK Government decided to abandon the Policing Pledge targets altogether in an attempt to give more local control to authorities ([13] Bullock, 2010).

Threats to the continuity of organizational identity triggers resistance that stands in the way of successfully implementing the required changes. Sometimes the resistance is unable to stop the implementation but slows down the change process. [31], [32] Hannan et al. (2003a, b) argued that such change processes appear as if the moves were carried out in a high viscosity medium – every single step taking immense efforts and being slower and more costly than expected:

P9. Leadership can facilitate change processes by understanding reasons for local resistance and to translate the resistance into more adequate change implementation or adjustments to the change plan.

P10. Slowing down of organizational change processes due to resistance escalates opportunity costs. More managerial attention is needed to understand and address the resistance and little attention is left “to fly the plane”.

What would be required to prevent or overcome such perceptions and associated resistance is a clear message that the changes are internally driven (i.e. originate within the unit), and follow from, and are consistent with, the local unit’s mission and identity – or, in our unified theoretical framework’s terminology: are meant to restore fit. That is, when circumstances change, the way in which identity is enacted may change without the identity itself necessarily changing ([76] Van Knippenberg et al. , 2008). Or in other terms: sometimes organizations need to change to stay themselves:

P11. Organizational change aiming at adjusting the organization to environmental changes may be consistent with the organization’s identity, rather than being in conflict with it. Changes that are consistent with the organizational identity will be easier and bear less opportunity costs than changes that are in conflict with the organization’s identity.

A social identity analysis of leadership ([75] Van Knippenberg and Hogg, 2003) has identified a number of aspects of leadership that are particularly important in understanding how leaders can provide a sense of continuity of organizational identity. First, leaders have to be perceived to embody the organizational identity – to be representative of “who we are”, and to be “one of us”. Second, leaders need to espouse visions of change that are also visions of continuity of identity. Without a clear message that “we will still be us, despite all changes” visions of change are likely to elicit resistance more than enthusiasm. Third, leaders need to act as role-models in the enactment of these changes – taking the lead in the change process not only verbally, but also behaviourally:

P12. Effective organizational change leaders embody the organizational identity, espouse visions of change that are also visions of continuity and role-model the enactment of the change.

What is seen as representative of the police identity, will likely differ from country to country and from force to force and from special unit to special unit – there is no “one size fits all” here. Yet, at the same time, the key mechanisms driving the underlying process remain the same, and these underlying process mechanisms need to be captured in combination with country-specific expressions of the collective identity – again, quite a balancing act indeed.

Performance and organizational legitimacy: the outcomes component

The ultimate question is how organizational change affects organizational performance. The effects of organizational change can be negative, neutral or positive. This relates to the output dimension of our unified theory of organizational change. In this context, our theory emphasises the critical role of two important mediating effects: the impact of organizational change on external legitimacy and internal identity. The argument is that if not executed carefully, organizational change is very likely to lead to external legitimacy erosion and internal identity conflict. These, in turn, will impact organizational performance negatively:

P13. A key external threat to the success of organizational change is legitimacy erosion, and a key internal threat is identity conflict, both generating a negative effect on organizational performance.

This closes the circle of our unified theory of organizational change, as these key mediation feedback effects will distort the organization’s fit with the environment.

On the one hand, the external consequences are reflected in the organization’s legitimacy in the broader environment. If the organizational change negatively affects the organization’s accountability, reliability and performance in the eyes of external audiences, the organization’s legitimacy may be severely harmed ([36] Hannan and Freeman, 1984). For instance, if the introduction of community policing comes with a ‘soft’ image of police officers, street crime might increase rather than decrease and media reports about police activities might become critical with the tendency to undermine the police authority even further. Still, when a “soft” policing image, translated as being trusted by the community and serving the public is aligned with the greater societal expectation, such an approach might effectively decrease street crime, since the police can rely on public and media support and co-operation. Such disruptive or constructive performance and legitimacy effects feed back into the external opportunities and threats.

Organizational change triggering internal organizational identity conflicts can lead to low work satisfaction and a lowered organizational identification. When police officers are led into directions that go against their identity, this might lead to a threat of their identity. When a traditionally community oriented police force is expected to produce a specific number of tickets for minor offences (i.e. speeding, biking without a light, walking over red traffic lights), this can undermine both, a core aspect of their identity, but also their legitimacy in the wider public.

Discussion

Organizational change is a major challenge; the literature is full of contributions outlining the multi-complexity of organizational change endeavours. It is widely acknowledged that planned organizational change is not fully possible, since “[o]rganisations are continually changing, routinely, easily and responsively, but change within them cannot be controlled arbitrarily. Organizations rarely do exactly what they are told to do” ([50] March, 1981, p. 563). We are aware that our model implies an ambitious programme for organizational change studies. Interdisciplinary discourse and cross-cultural research frameworks are challenging in themselves ([66] Sauquet and Jacobs, 1998; [72] Turati et al. , 1998). We feel that it is worth the effort and that existing theories in organizational change need to be systematically tested and modified in an international arena.

At the heart of our model lie the three observations with which we started. First, organizational change can violate the organizational identity, which might have detrimental effects on the organization’s legitimacy and performance. Second, to predict such effects, a contingency perspective enables us to analyse the specific external and internal conditions of organizations that facilitate both change success and change failure. Third, the general patterns and mechanics apply to all change processes. Nevertheless it is the very spirit of our contingency perspective that in an international context the meanings of patterns and mechanics that lie behind the input, throughput and output processes of organizational change can widely differ and therefore deserve not a cure-all approach, but a careful and respectful analysis of the specific contexts.

The two next contributions to this special issue introduce the first results from a large EU-financed international project into organizational change in police organizations. This project involves teams from ten different countries: Belgium, Czech Republic, France, Germany, Italy, Republic of Macedonia, The Netherlands, Romania, Spain and the UK. The research project “Comparative Police Studies in the EU (COMPOSITE; see www.composite-project.eu/) runs in the period from 2010 to 2014 collecting rich multi-level data to explore Figure 1 [Figure omitted. See Article Image.]’s unified, multidisciplinary and multi-level framework of organizational change in police forces in the ten participating countries. In this special issue, next to this paper’s introduction of the framework, initial findings from two work packages will be presented. The next paper in this special issue summarises the results from the joint efforts of the complete COMPOSITE team to systematically carry out an environmental scan analysis in all ten European countries, focusing on evaluating the O and T pillars of a SWOT framework from the perspective of specific police forces. The paper after that discusses issues that relate to the key role of technology.

The authors would like to thank the project partners for their contribution to this work. This research is partially funded by the European Commission in the context of the COMPOSITE project (FP7 contract no. 241918).

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Further Reading

1. Bamberger, S.G., Vinding, A.L., Larsen, A., Nielsen, P., Fonager, K., Nielsen, R.N., Ryom, P. and Omland, Ø. (2012), “Impact of organizational change on mental health: a systematic review”, Occupational Environmental Medicine, Vol. 69 No. 8, pp. 592-598.
2. Stone, M.M., Crosby, B.C. and Bryson, J.M. (2010), “Governing public-nonprofit collaborations: understanding their complexity and the implications for research”, Voluntary Sector Review, Vol. 1 No. 3, pp. 309-334.
3. Jacobs, G., Keegan, A., Christe-Zeyse, J., Seeberg, I. and Runde, B. (2006), “The fatal smirk”, Insider accounts of organizational change processes in a police organization, Journal of Organizational Change Management, Vol. 19 No. 2, pp. 173-191.
4. Mouhanna, C. (2008), “Police: de la proximité au maintien de l’ordre généralisé?”, in Mucchielli, L. (Ed.), La frénésie sécuritaire. Retour à l’ordre et nouveau contrôle social, pp. 77-87.
5. Peli, G.L., Pólos, L. and Hannan, M.T. (2000), “Back to inertia: theoretical implications of alternative styles of logical formalization”, Sociological Theory, Vol. 18 No. 2, pp. 195-215.

Appendix

Corresponding author

Gabriele Jacobs can be contacted at: gjacobs@rsm.nl

AuthorAffiliation

Gabriele Jacobs, Rotterdam School of Management, Erasmus University Rotterdam, Rotterdam, The Netherlands

Arjen van Witteloostuijn, University of Antwerp, Antwerp, Belgium, Tilburg University, Tilburg, The Netherlands, and Utrecht University, Utrecht, The Netherlands

Jochen Christe-Zeyse, Fachhochschule der Polizei Brandenburg, Brandenburg, Germany

Illustration

Figure 1: A unified framework of organizational change

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