Complexity, Organizations and Change (Routledge Studies on Complexity in Management)


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Please note that instructors are subject to change and not all instructors teach in each session of the program. John Van Maanen is the Erwin H. He works within the fields of organization behavior and theory. Van Maanen is an ethnographer of organizations ranging in type from police organizations to educational institutions, as well as a variety of business firms.

He is the author of numerous books and articles, most recently, Tales of the Field University of Chicago Press, , 2nd edition. Emilio J. Castilla studies how social networks influence organizational and employment processes and outcomes over time. He tackles this question by examining different empirical settings with longitudinal datasets, both at the individual and organizational levels. His focus is on the hiring, retention, and job mobility of employees within and across organizations and locations, as well as on the impact of teamwork and social relations on performance.

CRC Press Online - Series: Routledge Studies in Complexity and Management

His research and teaching interests include organizational theory and behavior, economic sociology, and human resources management. Castilla joined the MIT Sloan faculty in , after being a faculty member for three years in the management department of the Wharton School at the University of Pennsylvania. Currently she is investigating the design and management of the workplace to understand how organisations use digital capabilities internally to create more effective ways of working, and the impact of new ways of engaging with talent in the digital era.

Kristine previously held management roles in the tourism and airline industries in Australia, New Zealand, and the UK. She directs a team of more than scientists, engineers and laboratory technicians who develop and run DNA sequencing production processes. She oversees daily operations of the Labs, IT, and Engineering as well as new project and new process execution that keep this organization at the front edge of an industry where changing technology and speed are critical.

She is also Six Sigma, Black Belt certified and works across many boundaries between the science, technology, process development and operations applying her expertise in Visual Management systems and Dynamic Work Design. Roberto M. Fernandez is the William F. Fernandez currently serves as the co-director of the Economic Sociology PhD Program and served as the head of the Behavioral and Policy Sciences area from His research focuses on the areas of organizations, social networks, and race and gender stratification.

Fernandez has extensive experience doing field research in organizations, including an exhaustive five-year case study of a plant retooling and relocation. His current research focuses on the organizational processes surrounding the hiring of new talent using data collected in 14 organizations. He is the author of more than 50 articles and research papers published in top academic journals in his field.

Elsbeth Johnson is an expert in leadership, strategy and change. She began her career as an investment banker, first in corporate finance for Barclays Capital and latterly as a sell-side equity analyst at Deutsche Bank. She now splits her time between teaching and advisory work. When not in School, she works with organisations and their leaders, providing them with strategic advice, facilitation and executive development. Johnson was educated at Cambridge and London universities. These findings were consistent with a review by Sturmberg et al.

Background

Like Pollack et al [ 19 ], Sturmberg et al. Notwithstanding, social science researchers use complexity in a metaphorical manner whereas computer science and mathematics use complexity for quantitative modeling. Researchers are increasingly incorporating complexity theory in health services research despite ongoing debate on how best to do it [ 21 — 23 ].

There are no reviews exploring how complexity theory has been incorporated in the broader health services research literature related to nursing, medicine, and allied health. The purpose of this scoping review is to explore how complexity theory has been incorporated in health services research. In doing so, we answer the following research questions:. What research questions and phenomena of interest do researchers focus on when using complexity theory?

How are researchers using complexity theory within health services research Footnote 1? We anticipated heterogeneous studies in terms of research purposes, phenomena of interest, methods, participants, and context. Likewise, although we aimed to conduct a broad, replicable, and systematic search of published literature, we did not seek to appraise and synthesize research evidence. Therefore, a systematic review was not warranted. Scoping reviews involve five steps: a identifying the initial research question; b identifying the relevant studies; c selecting the studies; d charting the results; e collating, summarizing, and reporting the findings; and f consulting stakeholders for knowledge translation of findings [ 25 ].

Given the breadth of complexity theory, combined with a lack of agreed upon nomenclature, we anticipated literature to be indexed under a variety of terms. To account for broad indexing, we used a range of search terms often associated with complexity theory. We used citation searching when key articles were found. A study was eligible for inclusion if: a it was published in a peer-reviewed journal, b it was written in English, c authors provided a statement somewhere in their manuscript reporting they incorporated complexity theory within their research, d authors studied a phenomena related to health services research, and e authors included nurses, physicians, or allied health professionals.

Articles describing quality improvement projects were excluded, but articles describing quality improvement research or research on quality improvement techniques were included. We excluded articles describing quality improvement projects because the focus of quality improvement projects differs from that of research, with the former focused on descriptions of how a group worked to improve care for a specific population or organization and the later focused on developing new and often generalizable knowledge [ 28 ].

Our focus is on complexity theory in health services research , thus we excluded descriptions of quality improvement projects. Distinguishing between quality improvement and research reports is difficult [ 29 ]. To assist, we used criteria described by Newhouse et al. For criterion d , we used the Canadian Institute of Health Research definition of health services research [ 30 ].

We excluded studies that used complexity theory to explain aspects of diseases e. Likewise, we excluded studies offering commentary or discussion articles on how complexity theory could be used in research. For criterion e we defined allied health professionals as dietitians, occupational therapists, pharmacists, physiotherapists, and speech-language pathologists.

If studies involved more than the seven professions listed above, they were included only if they focused primarily on nurses, physicians, or allied health professionals. For studies with multiple professions, when possible, we included only the results pertaining to the seven professions above. Studies were excluded if they focused solely on pre-licensure students. We had no historical date limits. DT independently screened titles and abstracts. Articles that met inclusion criteria were then reviewed a second time using full text. If questions arose related to article eligibility, a second author DS reviewed the article.

The second author DS , who is familiar with the complexity literature, reviewed the final list of included studies. The list of articles was sent to a third party expert in the field of complexity for review. Data was entered into a Microsoft Excel spreadsheet and individual tables constructed for analysis.

Data included authorship, publication year, country of research, research design, professions involved, setting of research e. In keeping with a scoping review approach, we did not assess the methodological quality of included studies. We created a framework guided by our five research questions. First, we created a data table for study characteristics, including first author, year published, country, and study design.

Second, we created a data table outlining the professions involved, the area of research, the setting of research, and whether the research focused on interprofessional collaboration or education. From these tables we compared characteristics, setting, and profession across all studies to answer our first two research questions. Third, we categorized studies based on their research purpose using the verb presented by the researcher s in their purpose statement e. While verbs may overlap when referring to research purposes e.

Specifically, we reviewed all research purposes and identified common phenomena of interest. This provided us with a means to categorize studies by research purpose and then compare how the phenomena of interest differed within and between each category thus answering our third research question. Fourth, we reviewed each study and identified how researchers used complexity theory in their study e.

Collectively, this approach allowed us to answer our fourth research question. Finally, we created a data table containing the description of complexity theory from each study. From this, we determined the attributes of complexity theory used by each group of authors. To organize the attributes, we followed an approach used by Wallis [ 13 ] in his review of complexity in the organizational theory literature. Specifically, we extracted descriptions of the attributes i.

For example, we combined relationships and connections as one attribute: relationships.. We then looked for common themes between descriptions. After reviewing titles and abstracts, articles remained. Common reasons for study exclusion included: a the article was a commentary or debate on the use of complexity theory, b the authors used complexity theory to describe an aspect of a disease e. Most studies were qualitative [ 31 — 56 ], followed by quantitative [ 57 — 70 ], and, finally, to a lesser extent, mixed methods [ 71 — 73 ].

Case studies were the most common qualitative [ 31 , 32 , 34 — 37 , 40 — 42 , 44 , 45 , 47 , 50 , 51 , 55 , 63 , 74 ] and mixed method [ 71 — 73 ] design. Action research [ 48 ], ethnography [ 39 ], grounded theory [ 46 , 53 ], and phenomenological designs [ 43 , 49 ] were used less frequently. Two authors did not identify a specific qualitative design [ 54 , 56 ]. There was a mix of designs across the quantitative studies including, in order of frequency, cross-sectional [ 57 , 58 , 60 , 66 , 69 ], randomized controlled trials [ 61 , 62 , 70 ], retrospective [ 64 , 67 ], prospective cohort [ 63 ], systematic review [ 65 ], and unclear [ 68 ].

The majority of health services research conducted using complexity theory was based in the United States [ 31 , 32 , 34 , 36 , 37 , 42 , 43 , 46 , 50 — 63 , 65 , 66 , 68 — 70 , 73 , 74 ], followed by the United Kingdom [ 40 , 41 , 49 , 64 , 71 ], Canada [ 44 , 56 ], Norway [ 33 , 39 ], Brazil [ 38 ], Congo [ 45 ], Finland [ 67 ], Italy [ 47 ], Malta [ 35 ], South Africa [ 48 ], and Sweden [ 72 ].

All of the seven professions listed in our inclusion criteria were represented in our review.


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The settings studied using complexity theory consisted of long term care facilities [ 32 , 34 , 36 , 37 , 39 , 42 , 51 , 54 , 57 , 59 — 61 , 69 , 70 ], primary care [ 31 , 33 , 40 , 41 , 44 , 46 , 47 , 50 , 55 , 62 , 68 , 71 ], hospital [ 35 , 38 , 43 , 45 , 52 , 53 , 58 , 63 , 64 , 66 , 67 , 73 , 74 ], community health centres [ 48 , 62 , 74 ], and other e. Authors used a variety of research purposes to study an assortment of phenomena using complexity theory.

Two studies had two phenomena of interest based on our coding scheme [ 44 , 58 ]. Of these, two studies [ 36 , 51 ] listed a second purpose of exploring. Similar to the exploratory studies, we grouped studies based on the phenomena of interest. One study described aspects solely related to management e. Due to the low number of studies, we narratively report the results. Specifically, they examined features of practice related to patient centeredness using a secondary analysis of qualitative data. They concluded that attributes of complexity theory assisted them in examining how patient centeredness occurs within patient and physician interactions.

The second group of authors [ 65 ] examined change. They conducted a systematic review of interventions aimed at improving Type II diabetes. The authors assigned a value to each intervention based on the degree of complexity that the intervention exhibited. The authors used the degree of complexity to examine whether interventions based on complexity attributes were more effective than interventions that were not based on complexity. They concluded that interventions with a greater number of complexity attributes were more effective for changing diabetic outcomes. The third group of authors [ 69 ] also examined change.

These authors examined the degree of culture change practice adoption. They ranked culture change practices based on their degree of complexity and examined the degree of adoption. The authors concluded that less complex practices may be easier to implement and that implementation of less complex practices may improve implementation of more complex changes. Finally, Lanham and colleagues [ 74 ] used several attributes of complexity theory to re-examine two studies that evaluated the spread of effective interventions.

They concluded that self-organization, sense making, and interconnections could be used to facilitate the spread of effective practices. The research purposes that authors reported include advance and understand, analyze, compare, demonstrate, determine, document, estimate impact, evaluate, identify, implement, improve, produce, suggest, test hypothesis, and understand.

We categorized these studies based on phenomena of interest. In summary, based on our analysis of research purpose and phenomena of interest, studies aimed at exploring and studies aimed at describing represent the most common research purpose of health services research incorporating complexity theory.

There is a wide range of research purposes in the remaining studies. Within these remaining studies, the most common phenomenon of interest was change. Footnote 2 Examples include using complexity theory to conceptualize variables that were subsequently operationalized to determine if attributes of complexity account for rates in staff turnover [ 60 ], using complexity theory to conceptualize the work environment [ 43 ], and using complexity theory to conceptualize primary care organizations [ 40 ]. There was variation on how explicit authors were regarding how they used complexity theory as a conceptual framework.

Some authors described in detail the attributes they used and how they used them, whereas others stated that their research incorporated a complexity framework without describing which attributes or how complexity was used e. Examples of how complexity theory were used to in data analysis include comparing attributes of complexity e. Again, similar to those that used complexity as a conceptual framework, authors who used complexity as a data analysis framework varied in detail regarding what they used and how they used it.

Examples include using complexity to illustrate leadership principles [ 73 ], explain clinical governance [ 40 ], and hypothesize why an intervention worked to improve pain control [ 63 ]. The remaining three studies used complexity to predict change [ 64 ] or classify either interventions [ 65 ] or culture change practices [ 69 ].

Several authors reported dual applications of complexity e. Authors have incorporated a wide range of attributes from complexity theory to study phenomena related to health services research. To facilitate analysis, we grouped certain attributes into categories when authors appeared to refer to the same or similar concept of complexity. Wallis [ 18 ] used a similar approach in his review of complexity theory in organizational science. As complexity theory has no agreed upon definition and a myriad of concepts that comprise the theories subsumed within complexity theory, it was necessary to combine certain attributes to facilitate analysis.

Furthermore, it is beyond the scope of this review to offer a definition of each attribute. All of the studies except for two [ 31 , 63 ] incorporated a combination of attributes. Aita and colleagues [ 31 ] incorporated the concept of attractors to interpret secondary data and explore what is involved in patient-centered care within primary care settings.

Erdeck and Pronovost [ 63 ] introduced an intervention aimed at improving pain management that incorporated the concept of unpredictability i. Notably, in two studies, it was unclear what attributes of complexity the authors used [ 35 , 38 ]. A combination of three or four attributes of complexity theory was most common. The most attributes incorporated by a group of authors was six. This was done by six groups of authors [ 32 , 34 , 43 , 49 , 55 , 56 ].

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Within this group, emergence was included in all studies, followed by self-organization, feedback, agents within a system, non-linearity, and diversity. The remaining attributes appeared once or twice in various combinations. Although descriptions of complexity theory varied immensely across studies, it appears authors are describing complexity theory using aspects of the theory that capture how diverse relationships and communication between agents of a system can influence unpredictable changes within the system.

It comes as no surprise that descriptions often incorporate relationships, diversity, and communication. Likewise, descriptions also incorporate complexity attributes related to unpredictable changes with self-organization, emergence, and non-linearity being common in descriptions. The importance of capturing relationships and how those relationships contribute to changes in the overall system are apparent in the following examples of direct quotes of author descriptions:.

Change emerges through self-organization, defined as the mutual adjustment of behavior arising from interactions among staff as they meet immediate care demands [ 51 ]. Complexity science suggests that organizations, such as hospitals, are complex adaptive systems. As such, a hospital is defined as a set of connected or interdependent parts or agents—including caregivers and patients— bound by a common purpose and acting on their knowledge [ 58 ]. Complexity science, as related to healthcare, is the science of moving in a nonlinear and interactive manner where unpredictable outcomes are often realized; organizations are described as ever-changing collections of individuals and conditions in the organization; and patterns of interaction among individuals and connections are made in day-to-day practices among and between individuals [ 66 ].

This is the first scoping review to explore how complexity theory has been incorporated into health science research. Studies incorporating complexity theory appear to be increasing in frequency. Health services researchers are primarily using complexity theory with qualitative case studies conducted in the US focused on nursing and medicine in long-term care and primary care. Quantitative and mixed methods studies using complexity theory exist, and other settings are being studied, but both to a lesser extent.

Descriptions of complexity theory varied with 18 attributes of complexity theory across all studies in this review. The most common attributes were relationships, self-organization, and diversity. Descriptions appear to focus on aspects of complexity theory related to how diverse relationships and communication between individuals in a system may influence change. There is notable consistency between our findings and existing reviews.

Similar to Sturmberg et al. However, this expansion has largely remained at exploratory and descriptive level of research. In a review of complexity in computer science, mathematics, and management research, Pollack et al. Sturmberg et al. Despite 14 studies in our review being quantitative, there was minimal mathematical modeling. Although some studies in our review used modeling see for example [ 57 , 64 ], mathematical modeling using complexity theory does not appear common in health services research and the use of complexity theory remains at a descriptive or exploratory level. This is not surprising since complexity theory is primarily used as an explanatory theory as opposed to predictive one [ 76 ].

They argue a shift would enable researches to use complexity theory as a basis for quantitative modeling. Although we agree with Pollack et al.

Our findings demonstrate variation in how authors are incorporating complexity theory in health services research with a broad range of attributes being used. Thus, we align ourselves with Greenhalgh and colleagues [ 21 ] and suggest more adaptation and refinement is needed to determine how a complexity perspective can be used to answer health services research questions.

That is not to say mathematical modeling is not useful. As our review suggests, there is too much variation to be certain authors are talking about, even at a metaphorical level, the same concept. In a review of complexity in organizational science, Wallis [ 13 ] identified 20 definitions of complex adaptive systems containing 26 different conceptual components.

We found authors within our review used 18 different attributes of complexity theory. Although we used different labels than Wallis, overlap exists between common attributes used in organizational science and those used in health services research. Likewise, descriptions that focused on how diverse relationships and communication contributed to changes within a system are predominant. Using the most common collective attributes as an indicator for what researchers consider the most applicable components of complexity theory within a social sciences context provides a foundation to begin to develop a better understanding of each concept and how it can be used to comprise a complexity theory perspective in health services research.

Such foundational work is imperative. Many authors e. Likewise, many authors e. Davis and colleagues [ 15 ] suggest complexity theory is not a theory but more a perspective or way of thinking about certain phenomena. Although the transdisciplinary nature of complexity cannot be argued, the results of our scoping review and other reviews of complexity i.

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Indefinable theoretical perspectives can lead to studies with unclear or missing descriptions, implicit assumptions, and absent definitions. As a result, findings from such studies are difficult to generalize with confidence. Of course, all theories, especially transdisciplinary ones, require users to assume relationships that are, perhaps, untested. However, its use in knowledge translation, specifically health, requires an untested assumption that knowledge application in health is akin to classical diffusion theory [ 79 ].

A lack of description of how complexity is used in original research creates challenges for drawing conclusions across health services research using review methodologies e. For example, we excluded several studies where authors did not explicitly state they used complexity theory in their original manuscripts. This may have resulted in research that incorporated complexity from being excluded from our review. For example, Crabtree and colleagues have conducted a longstanding program of research using complexity theory that they outlined in a publication [ 80 ].

Such work represents a substantial contribution. Notably, these studies were not captured by our search strategy because they were not indexed using medical subject headings MeSH related to complexity nor did they have complexity as key words or titles. Consequently, they were captured by citation searching key articles located by our database searches. While such research has the potential to advance our understanding how to use complexity to answer important health services research questions, without clear and explicit descriptions of how complexity theory was used a priori in designing a study, it is difficult to know how to use complexity theory to design future studies.

Notwithstanding, papers by original authors offering a retrospective look back on their program of research from a complexity theory lens are helpful i. From this review, we stop short of recommending that complexity theory is more appropriate than other theories for incorporating into health services research.

Complexity is one of many theories researchers available to health services researchers. However, the findings of our review suggest that for researchers studying factors related to relationships, communication, and diversity—specifically how these factors may contribute to change within a system—other authors have found that complexity offers an appropriate choice. The appropriateness of complexity theory in studying systems stems from how it allows a researcher to conceptualize a system.

Specifically, complexity conceptualizes a system as non-linear and dynamical. Complex systems can be understood by comparison to complicated systems. Briefly, in a complicated system, the parts that comprise the system combine in predictable, knowable ways to comprise the overall system. If one were to conceptualize a health system as complicated, it would be possible to reduce the system and study the individual to gain an understanding of the overall system. If one studied enough components, one would know how the system works and therefore how to manipulate the system.

Such an approach has fallen short when studying health systems [ 87 ]. Instead, complexity theory offers a toolkit i. Complexity brings to the forefront the unpredictable nature of a complex system. Specifically, according to complexity, systems are still comprised of agents, but those agents interact with each other. The interactions of the agents are decentralized. From these interactions, changes occur within the system that may bring about additional change. One cannot trace the original cause of the change. So, while other theories offer tools for studying systems, many are based on the assumptions that systems behave like a complicated system, are predictable, and can be understood by studying components of a system.

The reason we stop short of suggesting complexity is more appropriate than other theories for studying health services research is because health systems are comprised of both complex and complicated systems. In some instances, depending on how the researcher conceptualizes the phenomena of study, theories that assume a complicated system are appropriate. However, instances where complex systems are involved, such as understanding how change may influence organizational culture, complexity theory offers an appropriate perspective.

Complexity theory is similar to other theories useful in health services research—especially theories aimed at exploring relationships in systems. Two such theories are systems theory and social network theory. Authors identify systems theory as being closely related to complexity theory [ 88 — 90 ]. Similar to complexity, systems theory also seeks to understand how relationships between agents of a system influence change.

However, according to Phelan [ 89 ], systems theory is focused on identifying and optimizing relationship characteristics whereas complexity is focused on understanding what influences interactions so that conditions may be created to support further interactions. In essence, complexity is more exploratory whereas systems theory is more confirmatory [ 89 ].

Social network theory offers a perspective of how relationships between individuals can influence the spread of something e. Using social network theory, researchers can map detailed relationships between entities for the purposes of describing and predicting how network structure may influence an outcome. In essence, the focus in social network theory is the connection of agents within a system. While complexity theory also offers a perspective on connections between agents, the focus of complexity takes a less reductionist view on interactions than social network theory.

Clearly systems theory, social network theory, and many other theories are appropriate for health services research. A choice of theory depends on multiple perspectives. As such, we stop short of suggesting complexity theory is more appropriate than other theories align ourselves with Davis and Sumara [ 90 ] to suggest complexity does not rise over other theories but instead rises among them. Variation across studies on how complexity is incorporated is expected. It is a product of intellectual grappling, experimentation, and exploration on how a complexity perspective can be incorporated to answer health services research questions.

In a sense, the findings of this scoping review represent evidence that the foundational work that so many authors urge is occurring. Although we are unable to determine what is appropriate use of complexity theory in health services research, the appropriateness of variation in the early stages of complexity applied to health services research is an expected finding of this scoping review.

There are several limitations in our review. First, related to our search strategy, we acknowledge that not all authors will agree our search terms are integral with elements of complexity theory. Second, this scoping review was conducted as part of a doctoral dissertation. As such, it was conducted primarily independently with a second reviewer when needed and, therefore, did not benefit from a team approach to scoping methodology see for example [ 26 , 94 ].

A solitary approach has been used in scoping reviews by other doctoral candidates e. Third, we included only studies published in English. The effect of inclusion and exclusion in systematic reviews by language is inconclusive [ 96 ], yet there is a possibility of excluding important studies from our scoping review—most likely related to the country of research origin.

Researchers are incorporating complexity theory in health services research. Researchers using complexity theory in health services research are primarily using the theory for various aspects of qualitative case studies e.

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Authors have employed many attributes of complexity and descriptions often incorporate aspects of complexity theory related to how diverse relationships and communication between individuals in a system can influence change. The overarching theme from this scoping review is variation. Although variation may be thought of as a drawback, variation may also be a product of applying a novel and malleable theory in a new context.

We do not yet know how best to incorporate complexity to study phenomena in health services research and the debate is far reaching. Perhaps there is no one method to apply this theory and its malleability permits broad application? That said, authors are attempting to study important phenomena using complexity theory and are grappling with how to use this theory. Although complexity theory shows promise in health services research and health services delivery, conceptual confusion and inconsistent application hinders the operationalization of this potentially important perspective.

Complexity appears particularly applicable for studying relationships and interactions between health professionals and management.

marcelina.userengage.io/18391-1998-nissan.php However, generalizability from studies that use complexity theory, at present, is difficult due to heterogeneity and variation in reporting. In summary, more research, debate, and exploration are still needed to continue to understand how complexity theory can be incorporated in health services research. The term use in this instance refers to how authors used complexity theory specifically in their study.

This differs from the term incorporated , which we use to refer to the broader use of complexity in health services research and to encompass all of our questions. Lapaige V. J Multidiscip Healthc. Thistlethwaite J. Interprofessional education: a review of context, learning and the research agenda. Med Educ. Zwarenstein M, Reeves S. Knowledge translation and interprofessional collaboration: Where the rubber of evidence-based care hits the road of teamwork. J Contin Educ Health Prof.

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A systematic review of the use of theory in the design of guideline dissemination and implementation strategies and interpretation of the results of rigorous evaluations. Implement Sci. A scoping review to improve conceptual clarity of interprofessional interventions. J Interprof Care.

Rycroft-Malone J. Nurs Res. The use of systems and organizational theories in the interprofessional field: Findings from a scoping review. Graham ID, Tetroe J. Best A, Holmes B.

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