organizational structure research paper

What do you mean by organizational structure? Acknowledging and harmonizing differences and commonalities in three prominent perspectives

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• Published: 11 October 2023
• Volume 13 , pages 1–11, ( 2024 )

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• Daniel Albert   ORCID: orcid.org/0000-0003-3888-1643 1  

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The organizational design literature stresses the importance of organizational structure to understand strategic change, performance, and innovation. However, prior studies diverge regarding the conceptualizations and operationalizations of structure. Organizational structure has been studied as an (1) arrangement of activities, (2) representation of decision-making, and (3) legal entities. In this point-of-view paper, the three prominent perspectives of organizational structure are discussed in terms of their commonalities, differences, and the need to study their relationship more thoroughly. Future research may not only wish to integrate these dimensions but also be more vocal about what type of organization structure is studied and why.

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Introduction

An important area of research in the organization design literature concerns the role of structure. Early research, including work by Chandler ( 1962 , 1991 ) and Burgelman ( 1983 ), has studied how strategy execution depends on a firm’s structure, and how that structure can influence future strategies. Moreover, prior work has explored organizational structure and its connection to strategic change (Gulati and Puranam 2009 ), performance (Csaszar 2012 ; Lee 2022 ), innovation (Eklund 2022 ; Keum and See 2017 ) and internal power dynamics (Bidwell 2012 ; Pfeffer 1981 ), among others.

What is surprising is the divergence in understanding what constitutes and defines organizational structure. This becomes particularly apparent when considering how structure has often been operationalized in prior studies. While there are a variety of conceptual and empirical approaches to organizational structure, this point of view paper focuses on three particularly prominent perspectives. Scholars of one stream of operationalization have argued that structure is how business activities are grouped and assessed in the form of distinct business units (or divisions) (Karim 2006 ; Mintzberg 1979 ), which may represent a company’s operating segments for internal and external reporting (Albert 2018 ). In another stream of operationalization, scholars argue that structure is inherent in the organizational chart, specifically, the chain of command and the allocation of decision-making responsibilities. Often, a simple yet powerful proxy has been to consider the roles assigned to the top management team members (Girod and Whittington 2015 ). Finally, a third type of operationalization of structure is the composition and arrangement of legal entities (Bethel and Liebeskind 1998 ; Zhou 2013 ), specifically, discrete subsidiaries constituting an organization’s business activities. This may be the most consequential understanding of structure as it relates to the containment of legal responsibilities.

These three perspectives overlap in some cases but may also characterize organizational structure differently in important ways. In a clear-cut case, a firm may consist of a top management team that perfectly reflects its business divisions and units, reported by consolidated but legally distinct entities. However, when examining the financial filings of different corporations, a different picture emerges as such clean alignment is often not the case. Not only are well-studied differences in the corporation's legal form (such as holding versus integrated) present, but top management responsibilities and reporting of business divisions often show that structure is indeed a multi-dimensional phenomenon in organizations.

To illustrate how different perspectives may lead to varying conclusions about organizational structure, two companies, the financial service firm Citigroup and the automotive company Ford Motor, are briefly discussed with respect to each perspective. Both Citigroup and Ford Motor are interesting cases, as they are large organizations with diversified business operations across various industry segments and a presence in multiple geographical markets. This complexity in business operations underscores the necessity of an organizational structure to implement and execute the firms' respective strategies.

The objective of this point of view is to emphasize and discuss the co-existence of fundamentally different measures and their underlying assumptions of organizational structure. These three perspectives highlight different aspects of organizational structure and can help reveal important nuances idiosyncratic to specific organizations. That is, complementing one perspective with one or two other perspectives can paint a more holistic picture of firm-specific structural designs. The “arrangement of activities” perspective provides generally a measure that captures sources of value creation, that is, the groupings of economic activities and knowledge. The “decision making representation” perspective provides generally a measure of hierarchical allocation of decision rights and has been likened to the level of centralization, that is, which responsibilities are specifically assigned to the highest level of decision-making. The “legal entities” perspective often captures decentralization as "truly" autonomous activities that can render integration more difficult and, therefore, imposes greater decentralization among such units.

A follow-up goal of this point of view paper is to discuss the implications and future research opportunities of clearly distinguishing between these perspectives in organizational design studies. A completely new area of research constitutes the inquiry of the relationships between these perspectives and whether and when alignment between the perspectives is enhancing or hindering performance, innovation, and strategic change. It is important to note that this point of view paper is not meant to provide an exhaustive list of perspectives of organizational structure, but to spark a constructive discussion around the theoretical and operational differences and commonalities between the arguably most prominent perspectives. Additional perspectives of organizational structure are discussed in the limitations section.

Three perspectives of structure

Structure as arrangement of activities.

This perspective suggests that groups of economic activities, managed and reviewed together, make up departments, units, and divisions that form the organizational structure (Joseph and Gaba 2020 ; Mintzberg 1979 ; Puranam and Vanneste 2016 ). In the middle of the twentieth century, Chandler ( 1962 ) observed that large American corporations not only diversified into a greater number of different business activities but also started to organize business activities into separately managed divisions, which are typically overseen by a corporate center unit. The organization of activities into compartments is often nested, that is, activities within a given compartment are further organized into subunits and so on. In a more general sense, such compartmentalization constitutes the division of labor (or specialization) in an organization, which can be organized along various dimensions. The most prevalent dimensions along which activities are organized into units include customer segments, products, geography, and functional domains, such as research and development, marketing, and sales activities (Puranam and Vanneste 2016 ).

The way activities are organized has been often related to archetypical designs, such as a more homogenous organization that is organized along functions and multi-divisional corporations that are more heterogenous in the activities making up business divisions (e.g., Raveendran 2020 ). The corporate center is often considered as a distinct unit of activities that holds the design rights of the organization, allowing it to organize these activities (Puranam 2018 ). The center may also play a coordinating role in the management of interdependencies between divisions to ensure alignment with corporate-level goals (Lawrence and Lorsch 1967 ) and foster value creation (Foss 1997 ).

Scholars of this perspective have studied how the arrangement of activities into compartments is associated with the propensity and type of reorganization (e.g., Karim 2006 ; Raveendran 2020 ), as well as its association with innovation outcomes (e.g., Karim and Kaul 2014 ). These two outcomes of interest are closely related, as compartments consist of employees and resources that constitute a source of knowledge that may be rearranged or combined with other units to address a (changing) market in novel and more efficient ways. Hence, this perspective may help to understand the sources of performance and innovation.

Illustration of arrangement of activities perspective

Figure  1 shows Citigroup’s operating business segments, which are in line with accounting regulations that require businesses to disclose operations in the way in which activities are managed internally and held accountable for cost and revenues (see Financial Accounting Standards No. 131). Accordingly, Citigroup operates three business segments, “Institutional Clients Group (ICG)”, “Personal Banking and Wealth Management (PBWM)” and “Legacy Franchises”, which are predominantly groupings of economic activities based on customer segments (i.e., institutional clients, private clients, and consumer clients). These groupings encompass various activities around this customer segment and the relevant product offerings. For example, the division Personal Banking encompasses activities for retail clients, such as Citibank’s physical retail network and online banking as well as private wealth operations for high-net-worth individuals. The respective segments may be understood as the organization’s business divisions, whereas further, nested, groupings exist within these divisions (e.g., U.S. Personal Banking constitutes a subunit with further subgroupings into Cards and Retail Banking operations). Supporting activities and operations that are not part of one of the three divisions are managed by the corporate center unit.

Citigroup’s operating business segments. This figure is the author’s own drawing but entirely based on Citigroup’s 2022 10-K report (page 2)

In Table 1 , the operating business segments are shown for the automotive company Ford. Accordingly, Ford operates six main segments (and one reconciliation of debt segment), “Ford Blue”, “Ford Model e”, “Ford Pro”, “Ford Next”, “Ford Credit”, and “Corporate Other”. These groupings encompass various product and customer segment activities, such as the “Ford Blue” legacy business of internal combustion engine automotives, under the Ford and Lincoln brands. Electric vehicle-related activities are grouped under “Ford Model e”, whereas “Ford Pro” groups activities to address corporate clients who seek to optimize and maintain fleets. Noteworthy is also the segment “Ford Next”, which is a grouping of investment activities into emerging business models. While these segments (i.e., divisions) encompass various activities, information is limited with respect to any nested groupings within these segments (or a potential lack thereof).

Structure as decision making representation

This perspective suggests that the job roles in the top management team (TMT) are reflective of the organizational structure, as executives are charged to oversee certain activities (Girod and Whittington 2015 ; Guadalupe et al. 2013 ). At first glance, this understanding is fairly similar to that of the arrangement of activities. At a closer look, however, the TMT structure perspective is more indicative of an information processing perspective. At the center of the information processing perspective lies hierarchy as a mechanism to cope with information uncertainty and resolve conflicts (Galbraith 1974 ). Moreover, information processing has long been considered as the way in which key decision-makers can ensure coordination and integration of units (Joseph and Gaba 2020 ). That is, the top management roles may in fact extend beyond the formal task structure and include the reintegration and coordination of activities more broadly.

The assignment of decision-making responsibilities can reveal how the organization “thinks” about interdependencies, such as the need to coordinate resources, the potential to leverage synergies and so forth. For example, roles that largely define autonomous areas of business allow managers to make decisions more independently from one another. In contrast, roles that are focused on dedicated functions, such as research and development, marketing, and finance often require greater coordination among managers (e.g., Hambrick et al. 2015 ). Hence, the decision-making representations in the top management team may be understood as a hierarchy mechanism to manage and even create interdependencies between activities. A case in point is the deliberate assignment of creating synergies between otherwise standalone units, for example, in the form of executives holding multiple roles that span several divisions.

While the assignment of decision-making responsibilities clearly relates to efforts of coordination and integration, it can also explain the emergence of internal power and politics dynamics (Cyert and March 1963 , Pfeffer 1981 ). For example, Romanelli and Tushman 9/14/2023 7:00:00 PM suggest that top management turnover is a measure of power dynamics in organizations and treat this as entirely distinct from organizational structure. Moreover, the upper echelons perspective has proposed that organizational choice and strategic outcomes are, at least in part, a direct reflection of the backgrounds of the leadership's individuals (Hambrick and Mason 1984 ), which suggests that design choices, such as organizational structure are decided under the auspice of the very same individuals (Puranam 2018 ) that researchers have used as a proxy to measure organizational structure. This emphasizes the importance of considering the TMT as a structure of decision-making representation rather than a measure of division of labor.

Perhaps it is this representational role of the TMT as a potential liaison between activity arrangements and decision-making, which Gaba and Joseph ( 2020 ) discuss as information processing, that has led some of the prior research argue that structure influences how decisions come about. Accordingly, decisions of reorganization and internal resource allocation are the result of a political negotiation process (Albert 2018 ; Bidwell 2012 ; Keum 2023 ; Pfeffer 1981 ; Pfeffer and Salancik 1974 ). Hence, this perspective may help understand the role of structure as a process that shapes decisions (Burgelman 1983 ).

Illustration of decision-making representation perspective

Table 2 shows Citigroup’s executive leadership team with each member’s specific job title that reflects the decision-making responsibilities. The team is made up of executives responsible for specific business divisions (e.g., one member carries the title CEO of Legacy Franchises), some members oversee particular geographical regions (e.g., one member carries the title CEO of Latin America), other members represent specific subsidiaries (e.g., one member carries the title CEO of Citibank N.A.), and again others are in charge of corporate functions (e.g., one member carries the title Head of Human Resources).

Table 3 shows Ford’s executive leadership team. The team is made up of executives responsible for business divisions, such as “President Ford Blue”, “CEO, Ford Pro” and “CEO, Ford Next”. In addition, executives represent particular activities of these divisions, such as “Chief Customer Officer, Ford Model e” and “Chief Customer Experience Officer, Ford Blue”. Similar to Citigroup, at Ford executives also represent geographical activities and various functional activities. Moreover, one executive represents a legal entity (Ford Next LLC), which is also a business segment (activity grouping).

Structure as legal entities

This perspective suggests that structure is delineated by legal boundaries, such as discrete subsidiaries that make up an organization’s operating units. This may constitute the most consequential understanding of structure as it relates to containment of legal responsibilities.

Thus, empirical studies have operationalized legal entities as a proxy for divisionalization in organizations (Argyres 1996 ; Zhou 2013 ) and degree of decentralization of research and development responsibilities (Arora et al. 2014 ). The way organizations are legally organized may be motivated by liability concerns, tax advantages, shareholder voting rights, as well as international law and compliance consideration (Bethel and Liebeskind 1998 ). Nevertheless, organizing into legally separate units can have important consequences for the management of the organization, such as limited economies of scope (see ibid.). For example, Monteiro et al. ( 2008 ) describe how subsidiaries in multinational corporations can become “isolated” from knowledge sharing with the rest of the organization. This isolation from intra-firm knowledge flows leads these subsidiaries to more likely underperform compared to less isolated subsidiaries.

It is important to note that legal structure is not always at the discretion of the organization. For example, the financial and economic crisis of 2007/8 has led legislators in some countries to introduce laws that require system-relevant banks to organize certain activities and assets into separate legal entities that contain losses and allow quicker resolvability in case the government decides to step in and take ownership stakes of affected units (Reuters 2014 ).

Legal structures, specifically in the context of multi-national organizations, have been studied with respect to decentralized decision-making, local market adaptation, and dynamics between subsidiaries and the headquarters (Bouquet and Birkinshaw 2008 ). Another aspect of studying legal entities in organizational design relates to internal reorganization. Legally separated activities are not only more straightforward to evaluate (i.e., greater transparency) as they typically maintain their own balance sheets and income statements, but they may also be easier to divest or spin-off, which provides the organization with greater flexibility. For example, the legal reorganization of Google into Alphabet in 2015 legally separated Google’s activities from all its “other bets”, which were run as their own legal organizations, with the goal for greater transparency and accountability (Zenger 2015 ). Moreover, the separation of activities into legal entities may also affect how easy or difficult it is for the organization to endorse cross-unit collaboration and execute internal reorganization without changing legal forms. Coordination cost between separate legal entities are greater, as more formal and legally binding contracts may need to be set.

Illustration of legal entities perspective

Figure  2 shows Citigroup’s legal structure. Accordingly, the organization is at the highest level a Bank Holding Company, which legally owns two (intermediate) holding entities, “Citigroup Global Markets Holdings Inc.” and “Citicorp LLC”. Each of these two entities owns additional subsidiaries, which are largely organized by region (these may hold additional subsidiaries). This structure is quite different from Citigroup’s management of operating activities as none of the business divisions is reflected in the legal structure.

Citigroup material legal entities. This figure is the author’s own drawing and a slight adaptation rom Citigroup’s publicly available presentation material via https://www.citigroup.com/rcs/citigpa/akpublic/storage/public/corp_struct.pdf , accessed on March 23, 2023. The dark blue boxed refer to operating material legal entities. The four boxes that are within the grey dashed rectangle are branches of Citibank N.A

Table 4 shows a list of legal entities reported by Ford in its annual report. Many of these subsidiaries are focused on regional activities and/or credit-related activities, which may be due to regulatory requirements of operating consumer financing activities. The legal entity Ford Next LLC is also its own business segment (i.e., an arrangement of activities reported as a managed division) and directly represented in the executive team. The Ford example does not provide much detail on the exact ownership structure among subsidiaries, which generally is indicative of a legal hierarchical structure of the respective legal entities. However, Ford European Holdings Inc. appears to own European subsidiaries, such as Ford Deutschland Holding GmbH, which in turn is the legal entity that owns subsidiaries in Germany and so on.

A path forward

The study of the commonalities , differences , and relationships between the three perspectives of organization structure—i.e., structure as arrangement of activities, decision-making representation, and legal entities—offers great potential for the field of organizational design. Previous research has often focused on one of these dimensions at a time to study organizational structure, but each perspective plays an important role in organizing and influencing decision-making.

Commonalities

All three perspectives share central ideas of organizational design. First, there is the notion that tasks are grouped and kept separate . The arrangement of activities perspective suggests that economic processes are managed and carried out together when these influence one another. Thus, this perspective stresses the grouping of tasks most forcefully of all the perspectives. However, the two other lines of research also reflect groupings of tasks. The decision-making representation perspective considers job titles and decision-making authority assigned to distinct members of the executive team to generally be related to how tasks are structured. Decision makers, therefore, oversee a particular task environment. The legal entity perspective proposes legal boundaries as delineations of responsibility and accountability. That is, legal separation and containment of financial accountability constitute somewhat binding modularity.

The three views also embrace the concept of hierarchy , albeit manifested differently. The arrangement of activities captures hierarchy by stressing that activity groups (i.e., units) can be nested, that is, a division is made up of several sub-units with own task responsibilities. Hierarchy in decision-making representation is captured by reporting lines and may be more focused on hierarchy as a means of conflict resolution and the diffusion of top-down ideas. The legal entity view shares similarity with the arrangement of activities perspective in that nested structures of subsidiaries can exist, but the “mechanism” of hierarchy is the ownership structure.

Differences

While the three perspectives have obvious similarities and overlap—after all, that is why scholars rely on one or the other perspectives to proxy organizational structure—these perspectives also capture distinct elements and, therefore, draw attention to different theoretical aspects of organization structure. The arrangement of activities perspective draws attention to the locus of value creation and innovation associated with structure. The grouping of activities influences whether synergies can be realized, goals achieved more quickly (Raveendran 2020 ) and whether knowledge can be recombined to seize innovation opportunities (Karim and Kaul 2014 ). The representation of decision-making perspectives draws attention to the top management team as structural authority to resolve conflicts between lower-level decision makers, and lobby for distinct operating activities in the organization. Moreover, top management plays a crucial role in the restructuring of the arrangement of activities and decisions with respect to changing the composition of legal entities. For example, political power of executives has been argued and shown to affect division reorganization decisions (Albert 2018 ) and allocation decisions of internal non-financial resources (Keum 2023 ). Finally, the legal entities perspective draws attention to structure as legal accountability and draws a sharp line between what is truly separate and what is more ‘loosely’ integrated. Consequently, arranging activities as legally separate entities often requires more costly coordination measures, such as formal contracts.

Theoretical and empirical questions around these differences may investigate the following claims.

A research focus on organizational structure as arrangement of activities may be of particular interest for the aim of understanding performance and innovation outcomes as economic activities are directly related to the process of value creation.

A research focus on organizational structure as decision-making representation may be of particular interest for the aim of understanding how strategic goals are formed, with respect to change and associated corporate reorganizations.

A research focus on organizational structure as legal entities may be of particular interest for the aim of understanding barriers to integration and realization of synergies as well as flexibility with respect to changes in corporate scope.

However, these preliminary statements about the different perspectives on organizational structure are not meant to encourage researchers to keep them strictly separate. Instead, future studies can explore these perspectives' theoretical relationships, offering wonderful opportunities for new insights, as will be discussed next.

Relationships

By investigating underlying connections between the different perspectives, future research may surface important insights about organizational design that can open up entirely new research programs. An essential theoretical question involves whether there are any directional relationships between specific perspectives. For example, when does top management team structure induce or follow other changes (in divisions and legal structure)? Karim and Williams ( 2012 ) show that changes in executives’ division responsibilities helps predict subsequent reorganizations in the respective units. Another question is how the legal structure may affect the arrangement of activities over time. The greater cost of integration of legally separate entities may imply that greater autonomy is more likely to follow, which future research may want to investigate.

Moreover, it would be useful for the field of organizational design to better understand when potential structural changes in divisions and legal entities trigger in turn a reorganization of leadership responsibilities. The legal structure may change much more slowly than the other two types, because of regulatory and other legal reasons. Nevertheless, the legal structure can play an essential role in how the organization lays out its strategic priorities, is internally managed, and evaluates its performance. At least, these appear to be the main reasons of notable reorganization that lead to an overhaul in legal structure. Recent examples include the already mentioned case of Google’s legal reorganization into contained group subsidiaries under the Alphabet umbrella, Facebook’s legal reorganization into the corporation Meta (Zuckerberg 2021 ), and Lego’s reorganization into the Lego Brand Group (LEGO Group 2016 ). The question remains whether the legal reorganization is a means to enable better top management and divisional structures or whether the top management structure, for example, motivated such legal changes for better alignment.

Finally, a completely novel question that acknowledges the multifaceted perspectives of organizational structure emerges. What are the performance, innovation, and strategic change consequences for organizations when these different perspectives are aligned or misaligned? Are there specific “archetypes” organizational structures along these dimensions?

Implications

It is important to stress that in some cases it may be necessary to draw upon two or all three to gain a more holistic picture of organizational structure and important nuances that may be highly specific to a particular organization. Whereas the arrangement of activities provides an overview of distinct operating units, such as divisions and subunits, this perspective alone does not capture complex interrelationships with respect to who reports to whom. This becomes most critical in cases of a matrix organization, where, for example, a segment is guided by a product goal as well as some geographical goals.

Moreover, a comparison of some of the organizational structure characteristics between Citigroup and Ford demonstrates how important, potentially strategy-influencing differences exist when consulting all three perspectives. For example, the fact that Ford’s executive team is in part made up of executives who represent a specific legal entity, which is its own reporting segment, suggests that legal structure, decision-making and value creation for certain parts of the organization go hand in hand. In contrast, Citigroup’s legal structure bears little to no resemblance to its operational structure. This may suggest that in Citigroup’s case legal entities play a very different role for organizational design purposes, such as containing legal regulatory requirements and legal containment of liability, whereas its management of value creating activities and decision-making responsibilities is guided across these legal boundaries. Concluding that the legal structure is a reflection of operational and strategic design may be somewhat misdirected with respect to product-market operations but more reflective of risk and geographical profiles in Citigroup’s case. Future research is encouraged to explore such differences in more detail.

Limitations

Before concluding this point of view paper, it is important to acknowledge that there are other important attributes of organizational design and structure that should be considered. For example, the leadership perspective of structure may be extended or complemented by considering the structure of corporate governance and its effects on organizational changes (Castañer and Kavadis 2013 ; Goranova et al. 2007 ). Moreover, the arrangement of activities into departments, units, and divisions determines the formal structure of the organization. Employees who belong to the same department (and work on the same task) often work in the same physical location and, therefore, are more likely to interact (including outside their formal task) and form (informal) networks with those close to them (Clement and Puranam 2018 ). As such, the structure of tasks can affect the emergence of networks in the organization. Organizational changes to the arrangement of activities may consequently conflict with the informal structure that has formed over time (Gulati and Puranam 2009 ). Informal networks in the organization may, therefore, constitute another “measure” of structure, but this paper takes the perspective that networks are a more likely to be a consequence of organizational structure (albeit one that may affect future structures).

Finally, organizational design can exceed a focal firm’s boundaries. Partnerships, such as alliances, joint ventures, and meta-organizations (Gulati et al. 2012 ), pose additional challenges in determining the actual structure of an organization. Future research is advised to study how different dimensions of organizational structure extend to and impact such boundary-spanning multi-organization designs.

The divergence in prior literature with respect to conceptualizing and operationalizing organizational structure reveals that this construct has more facets to it than sometimes acknowledged. Studying the alignment and divergence of these three characteristics of structure within organizations has potential to qualify and complement prior theories and generate new insights with respect to nuances of organizational design that we may have overlooked in prior work. It is important to consider that focusing only on one of these dimensions at a time for studying structure can indeed be sufficient. However, the field of organizational design may wish to be more concise in which perspective is chosen and why, when building, testing, and extending theory. Highlighting what is not measured following a particular perspective can already enrich our understanding of the role of organizational structure in novel and impactful ways.

Data availability

Data used in this manuscript are publicly accessible through regulatory filings and company Investor Relations websites.

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Acknowledgements

I appreciate the helpful comments and guidance provided by the handling editor-in-chief Marlo Raveendran and two anonymous reviewers. I also would like to thank all three editors-in-chief for supporting the publication of this point of view manuscript.

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Albert, D. What do you mean by organizational structure? Acknowledging and harmonizing differences and commonalities in three prominent perspectives. J Org Design 13 , 1–11 (2024). https://doi.org/10.1007/s41469-023-00152-y

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Structural dimensions and hypothesized relationships, dimensional research on organization structure: meta-analysis and conceptual redirection.

Published online by Cambridge University Press:  01 December 2021

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A previous meta-analysis of dimensional structure research published during the latter half of the 20th century revealed significant intercorrelation among structural dimensions inspired by Max Weber's bureaucratic ideal type, providing support for continued research on dimensional structures and for the bureaucratic structural model that served as its theoretical foundation. A new meta-analysis reported in this article, motivated by questions regarding the continued applicability of bureaucratic dimensional models in the later era of new organization forms, indicates that many of the interrelationships among five structural dimensions (formalization, standardization, specialization, vertical differentiation, and decentralization) have weakened since the time of the earlier meta-analysis. The results of this study, conducted using a sample of 346 correlations from a collection of 155 published articles, are interpreted as failing to provide consistent evidence supporting a central tenet of the bureaucratic structural model, therefore, as indicating that dimensional structural research now lacks a viable theoretical foundation.

An organization's structure consists of patterned regularity that is reproduced as its members interact and communicate about their interactions to coordinate actions and sustain the state of being organized. Research on organization structure originated in the mid-20th century, rooted in two translations of Max Weber's bureaucratic ideal type (Gerth & Mills, Reference Gerth and Mills 1946 ; Parsons, Reference Parsons 1947 ). As will be described more completely in the following literature review, it first took the form of qualitative case investigations (e.g., Burns & Stalker, Reference Burns and Stalker 1961 ; Gouldner, Reference Gouldner 1954 ; Selznick, Reference Selznick 1949 ), then evolved into quantitative research on structural characteristics (e.g., Aiken & Hage, Reference Aiken and Hage 1968 ; Hall, Reference Hall 1963a ; Pugh, Hickson, Hinings, & Turner, Reference Pugh, Hickson, Hinings and Turner 1968 ). In turn, these studies formed the foundation, during the 1970s and 80s, of a domain of research that grew to include hundreds of studies of dimensional relationships and effects (Donaldson, Reference Donaldson 2001 ). The dimensional models considered in this research consist of multiple continua that form profiles of structural attributes.

As research progressed on dimensional models of organization structure, so too did critical analyses that highlighted possible limitations in the ability of existing dimensional models to explain evolving structures and structural practices. Theorists proposed that the introduction of flexible work systems, self-managing teams, and similar organizational innovations would lead to the demise of then-current structures and the onset of greater autonomy and engagement (Heydebrand, Reference Heydebrand 1989 ; Kanter, Reference Kanter 1989 ). Researchers identified emerging trends in the use of various workplace involvement practices that appeared to support this position (e.g., Appelbaum & Batt, Reference Appelbaum and Batt 1994 ; Osterman, Reference Osterman 1994 ; Smith, Reference Smith 1997 ). Critics asserted that bureaucratic structural theory and dimensional models of organization structure were dated, if not dead (Clegg & Hardy, Reference Clegg, Hardy, Clegg, Hardy and Nord 1996 ; Morgan, Reference Morgan 1997 ; Pfeffer, Reference Pfeffer 1997 ).

Against these criticisms, other theorists countered that evidence from the field continued to support the viability of bureaucratic structural theory and the applicability of dimensional models of organization structure (e.g., Donaldson, Reference Donaldson 1996 ; Gazell & Pugh, Reference Gazell and Pugh 1990 ). A meta-analysis by Walton ( Reference Walton 2005 ) of research on dimensional models aggregated the results of research published prior to 1998 and provided cumulative evidence in support of bureaucratic theory's continued validity. Nonetheless, theorists continued to suggest that organizational innovations such as shop floor information technology and workplace automation threatened bureaucratic organization and related structural models (e.g., Boyer, Ward, & Leong, Reference Boyer, Ward and Leong 1996 ; Zammuto, Griffith, Majchrzak, Dougherty, & Faraj, Reference Zammuto, Griffith, Majchrzak, Dougherty and Faraj 2007 ). Arguably, the temporal span of Walton's meta-analytic sample failed to capture the duration required for the full effects of these innovations to be realized. Perhaps the threats to bureaucratic organization thought to be associated with these innovations did diminish the applicability and theoretical relevance of bureaucratic structural models and related dimensions in later years.

Structural dimensions and dimensional models continue to be incorporated in contemporary research, as substantiated by the recent studies collected for the analysis reported later in this article. It is assumed rather than questioned in this ongoing research that empirical relationships similar to those that produced Walton's findings are still evident, and, correspondingly, that bureaucratic structural theory and related dimensional models remain valid as a theoretical explanation for structural relationships and effects. Other than dimensional theorists' interpretation of Weber's ideal type, there is no widely accepted theoretical explanation for the collection of organizational characteristics codified as structural dimensions and for the relationships among these dimensions hypothesized in dimensional structural models. Absent continued empirical support for bureaucratic structural theory, contemporary dimensional models of organization structure lack essential theoretical standing.

The present article questions whether newer research continues to produce evidence of empirical relationships consistent with the findings of Walton's meta-analysis. Presented are a replication and an extension of Walton's study in which adjusted mean effect sizes from dimensional structure research published during the temporal span of Walton's meta-analytic sample are compared with adjusted mean effect sizes from dimensional structure research published subsequently. The issue addressed by this analysis is whether Walton's findings remain valid into the present and, as a consequence, whether dimensional models retain credibility as theoretical descriptions of current-day organization structures. Based on the results of this study, it is concluded that bureaucracy as interpreted in dimensional structural research no longer provides an incontestable theoretical foundation for structural studies. New research, examples of which are described in the article's closing discussion, is required to reestablish viable conceptual grounding.

Early in the development of the field of organization theory, a significant collection of studies of organization structure emerged that traced its conceptual roots to Max Weber's bureaucratic ideal type. Research in this stream was stimulated in large part by the publication of Parsons' ( Reference Parsons 1947 ) edited translation of Weber's Wirtschaft und Gesellschaft , wherein Weber identified a profile of features that constituted the bureaucratic ideal type. Mansfield ( Reference Mansfield 1973 ) summarized Weber's bureaucratic model (based on the Parsons translation) as incorporating six principles: fixed and official jurisdictional areas ordered by rules; a strict hierarchical system of authority; administration based on written documents; trained and expert management; affiliation requiring full-time occupational commitment; and management based on generalized rules.

A second translation of Weber's Wirtschaft und Gesellschaft , by Gerth and Mills ( Reference Gerth and Mills 1946 ), suggested six similar characteristics: selection and promotion according to expertise as opposed to friendship or favoritism; a hierarchy of authority in which superiors have the authority to direct subordinates' actions; rules and regulations that are unchanging, to provide the bureaucracy's members with consistent, impartial guidance; a division of labor in which work is divided into tasks that can be performed efficiently and productively; written documentation, to provide consistent guidance and a basis for evaluating bureaucratic procedures; and separate ownership, so that members cannot gain undeserved advantage by becoming owners. According to Mansfield ( Reference Mansfield 1973 ) and evident in both summaries, the critical element that separated Weber's bureaucratic ideal type from contemporaneous approaches to theorizing about organizations was bureaucracy's foundation in procedures specified and administered as impersonal, general rules.

Drawing from Weber's ideal type, initial studies of bureaucracy, conducted during the 1940s and 1950s, consisted of case analyses intended to examine potential advantages and unanticipated liabilities of the bureaucratic form of organization (e.g., Gouldner, Reference Gouldner 1954 ; Merton, Reference Merton 1940 ; Selznick, Reference Selznick 1949 ). Research in these early studies was based on an interpretation in which Weber's analytical construct was recast as a descriptive model, meaning that his ideal type composed of a set of elements constituting theorized bureaucracy was reinterpreted as a factual description of a suite of features observable in everyday organizations. In this way of thinking, real-world organizations could be more or less bureaucratic.

Subsequently, researchers from the late-1950s onward sought to develop generalized models of structure consisting of theoretical dimensions based on the results of early case studies and inspired by Weber's ideal type. Research in this later era took another step away from Weber's theorization by reconceptualizing the normative constants of Weber's ideal type as descriptive variables able to classify organizations and describe their structures. Based on the earliest dimensional research (e.g., Dimock, Reference Dimock 1959 ; Heady, Reference Heady 1959 ; Udy, Reference Udy 1959 ), Hall ( Reference Hall 1963a ) proposed a model of six bureaucratic dimensions: a division of labor based upon functional specialization; a well-defined hierarchy of authority ; a system of rules covering the rights and duties of position holders; a system of formal work procedures ; impersonality in personnel relations; and selection and promotion based on technical competence . In a study of questionnaire data obtained from members in 10 organizations, Hall verified that his six dimensions could be conceptualized and measured as continua and found that the dimensions appeared to show evidence of combinations unique to particular business functions (e.g., marketing, administration) but not to the age or size of the organizations studied. In a second study, Hall ( Reference Hall 1963b ) used the same six dimensions to examine differences among subunits within the 10 organizations and reported that hierarchy of authority, division of labor, and procedural specifications covaried with departmental purpose, and that hierarchy, division of labor, formal procedures, and impersonality had lesser effects among executives than among nonexecutives. Together, the two studies demonstrated that an organization's structure, both internally and as a whole, could be characterized by a multidimensional description and that this description was associated with organizational purpose in predictable ways.

In a second noteworthy stream of structural research, Blau ( Reference Blau 1965 ) identified nine characteristics of organization structure based on his interpretation of Weber's ideal type: size , the number of members, total assets, or resource capacity of the organization; complexity , the number of locations of operation, or the number of basic objectives or responsibilities of the organization; standardization , the extent to which formalized plans are followed in performing role or departmental responsibilities, and the specialization of those responsibilities; expertness , the proportion of the organization's members that are professionalized; the size of the administrative component , the proportion of personnel in administrative or staff positions; centralization , or the location of decision-making and consequent shape of the organization's structure; formalization , procedures stated as formal rules, indicated by the existence, size, specificity, and uniformity of written procedural documentation; impersonality , relations shaped by policy rather than relationship; and career stability , occupational longevity indicated by low organizational turnover and high length of service. Blau ( Reference Blau 1970 ) then examined the effects of decentralization, i.e., reduced centralized control, in organizations. Findings based on data from archival information and interviews conducted in 53 government employment agencies indicated that organization size, formalization, and standardization were all positively related to decentralization, suggesting that as the organizations in Blau's sample grew larger they also reduced centralization and substituted formalization and standardization as mechanisms of organizational control.

To originate a third stream of research on organization structure, Hage ( Reference Hage 1965 ) developed a model consisting of eight variables, four identified by Hage as organizational means and four as organizational ends. The four organizational means variables, described as structural dimensions in other theorists' models, were: complexity or specialization, reflecting the number of occupational specialties represented in the organization and level of training required; centralization , or hierarchy of authority and degree of participation in decision-making, including the proportion of jobs in the organizations involved in decision-making; formalization or standardization, the proportion of jobs in the organization that are codified and the range of variation allowed within jobs; and stratification , differences in status, income, and prestige among jobs and mobility among jobs and status levels. The four ends variables, identified as outcomes in other research, were: adaptiveness or flexibility, assessed as the number of new programs or techniques introduced in the organization during a year; production or effectiveness, the number and rate of increase in units of output produced per year; efficiency , the cost per unit of yearly output; and job satisfaction or morale, satisfaction with working conditions and rate of annual turnover. Hage then proposed eight propositions and 21 corollaries that mapped patterns of association among the eight organizational variables, and these 29 proposed relationships became the basis for hypotheses assessed in a series of studies of data collected from 16 social service agencies (e.g., Aiken & Hage, Reference Aiken and Hage 1966 ; Hage & Aiken, Reference Hage and Aiken 1967a , Reference Hage and Aiken 1967b , Reference Hage and Aiken 1969 ).

In a fourth major stream of structure research, the Aston group proposed a six-dimensional model intended to guide the group's research on organization structure (Hinings, Pugh, Hickson, & Turner, Reference Hinings, Pugh, Hickson and Turner 1967 ; Pugh, Hickson, Hinings, Macdonald, Turner, & Lupton, Reference Pugh, Hickson, Hinings, Macdonald, Turner and Lupton 1963 ). Dimensions included in Aston's model were: specialization , the division of labor within an organization, indicated by the number of specialized functions within the organization and by the degree of role specialization or narrowing down of the tasks assigned to each organizational role; standardization , including specification of the rules guiding decision-making, and the advance specification of roles, offices and titles, qualifications, performance measures, and rewards for performance; formalization , or the degree to which communication and procedures in the organization, including rules, roles, operational procedures, and decisions, are written down and preserved; centralization , or the location of decision-making processes and control systems, the site of the information used to make those decisions, and the location, frequency, and thoroughness of decision review procedures; configuration , the shape of the organization's authority structure including its verticality or number of levels of authority, segmentation into differentiated subunits, and the number of different positions in the various segments; and flexibility , referring to the amount, speed, and variability of change in the organization's structure.

The Aston researchers followed up with a collection of studies aimed at assessing and extending their conceptual model. Using data from a sample of 46 British organizations representing a variety of industries, Pugh et al. ( Reference Pugh, Hickson, Hinings and Turner 1968 ) examined a model including five of their six original dimensions (dropping flexibility), plus the additional dimension of traditionalism , defined as the presence of implicitly legitimized verbally transmitted procedures. Data were collected in key informant interviews in which each structural dimension was measured as a scale that was further divided into subscales corresponding with specific interview questions. Results indicated moderate to high positive correlations among formalization, standardization, specialization, and configuration. Correlations between these dimensions and centralization were smaller and negative, suggesting that the formalization of procedures and centralization of decision-making were alternative ways of exerting control over organizational objectives and processes in the organizations included in the Aston sample.

From these four streams of founding research, analyses of dimensional models of organization structure multiplied to include hundreds of published studies. Dimensional models inspired by Weber's bureaucratic ideal type became widely accepted as theoretically valid representations of organization structures and structural characteristics (e.g., Donaldson, Reference Donaldson 1996 , Reference Donaldson 2001 ; Gazell & Pugh, Reference Gazell and Pugh 1990 ; Mintzberg, Reference Mintzberg 1979 ). Beginning in the 1990s, however, theorists suggested that emerging forms of organization and organizational structures differed in significant ways from organizations and structures of prior years, leading to the question of whether formerly valid dimensional models would remain descriptive of organization structures of the 1990s and beyond.

Cited in support of this viewpoint were several surveys and analyses of new forms of organization. For example, Smith ( Reference Smith 1997 ), in describing US work organizations of the 1990s, noted a transition away from individualized work toward the use of teams, first as problem-solving groups (quality circles), and then as primary entities charged with task performance (self-managing teams). As work moved from individuals to teams, emphasis shifted from traditional structural stability and persistence to adaptability and empowerment. Flexible work systems were implemented to democratize decision-making and encourage experimentation and learning. Osterman ( Reference Osterman 1994 ) estimated that approximately 35% of US firms with 50 or more employees made substantial use of flexibility-enhancing organizational practices including quality circles, employee involvement programs, job enrichment, self-managing teams, and continuous improvement systems. Appelbaum and Batt ( Reference Appelbaum and Batt 1994 ) reported that 85% of Fortune 1000 companies were using at least one employee-involvement practice. Similar innovations were implemented throughout Europe following successful sociotechnical experimentation (e.g., Emery & Thorsrud, Reference Emery and Thorsrud 1976 ; Lindestad & Rosander, Reference Lindestad and Rosander 1977 ) and as part of the New Forms of Work Organization platform enacted by the European Union (European Commission, 1997 ; Longoni, Golini, & Cagliano, Reference Longoni, Golini and Cagliano 2014 ).

This new perspective shaped the context within which Walton ( Reference Walton 2005 ) conducted a meta-analysis of published research on organization structure. The stated purpose of Walton's analysis was to assess the continued relevance of the bureaucratic structural model of organizational control in light of then-recent criticisms. It focused on structural dimensions inspired by Weber's bureaucratic ideal type and often studied in the structure literature: formalization , the production and retention of written rules, regulations, and procedures (Pugh et al., Reference Pugh, Hickson, Hinings and Turner 1968 ); standardization , or the control and coordination of work through the application of uniform rules and procedures (Blau & Scott, Reference Blau and Scott 1962 ); decentralization , defined as the distribution of decision-making downward and outward in an organization's hierarchy (Pugh et al., Reference Pugh, Hickson, Hinings and Turner 1968 ); and differentiation , defined as the number of formally distinguished structural subunits (Blau, Reference Blau 1970 ). Walton further divided differentiation into task specialization , the degree to which work activities are subdivided and job scope is narrowed, leading to an increase in the number of job titles in an organization (Blau & Schoenherr, Reference Blau and Schoenherr 1971 ); vertical differentiation , or the number of hierarchical levels in an organization (Pugh et al., Reference Pugh, Hickson, Hinings and Turner 1968 ); and horizontal differentiation , the number of subunits or functional specialties within an organization. This subdivision resulted in a model of six structural dimensions.

Walton hypothesized that the six dimensions would be positively related to one another based on theoretical arguments inspired by Weber's bureaucracy and developed primarily by Peter Blau and associates. According to Walton's argument, limiting job scope through task specialization occurs in order to increase task performance and facilitate control by reducing the range of activities that must be learned, accomplished, and managed (Blau, Reference Blau 1970 ). In turn, growth in task specialization increases the number of jobs that must be performed to complete a given amount of work, leading to an increase in the number of managers required to retain effective spans of control, and this increase in managers leads to vertical growth in the hierarchy needed to supervise and coordinate their work (Blau, Reference Blau 1968 ). In this manner, horizontal subunits, each with its own manager, and hierarchical levels, each coordinating and controlling managerial activities in subordinate levels, increase in stride with specialization: the three forms of differentiation – task specialization, horizontal differentiation, and vertical differentiation – are interlinked and positively related .

Also according to Walton, Weber's bureaucratic ideal type specified that the authority required to perform work activities is distributed to those positions responsible for the activities' performance. As differentiation progresses, authority is distributed among an increasing number of positions, both vertically and horizontally, and decision-making is increasingly decentralized (Blau, Reference Blau 1968 ). Accompanying this decentralization, Weber's conceptualization also limits the authority distributed to positions by standardizing the rules, regulations, and procedures that stipulate the duties associated with those positions (Blau & Scott, Reference Blau and Scott 1962 ). Standardization emerges as limits on authority are imposed during the process of decentralization. Bureaucratic decentralization calls for concurrent standardization, and both increase as tasks become more specialized and the hierarchy more differentiated .

Finally, per Walton, standardization is accomplished through the work of staff specialists who develop and record the rules, regulations, and procedures required to coordinate and control the decentralized decision-making undertaken by the holders of specialized and differentiated positions (Mintzberg, Reference Mintzberg 1979 ; Pugh et al., Reference Pugh, Hickson, Hinings and Turner 1968 ). These staff specialists formalize organizational processes, committing them to writing and retaining written documentation for recurrent bureaucratic use (Pugh et al., Reference Pugh, Hickson, Hinings, Macdonald, Turner and Lupton 1963 ). Formalization develops in organizations as standardized rules and procedures, emerging during the process of differentiating activities and decentralizing decision-making authority, are documented and preserved. Formalized standards become substitutes for centralized supervision and direct control of organizational activities (Blau, Reference Blau 1968 ). Formalization produces the standardization required to manage the effects of decentralization due to increasing specialization and differentiation, both horizontal and vertical . In this manner, Walton theorized positive relationships among the six structural dimensions examined in his meta-analysis.

Walton tested his hypothesis of positive dimensional intercorrelation in a meta-analysis of correlations collected from articles published between 1963 and 1997. Using methods devised by Hunter and Schmidt ( Reference Hunter and Schmidt 1990 ), he found that the 15 effect size estimates representing every bivariate relationship among the six dimensions in his model were all positive, ranging in size from .37 to .75 with an average size of .54, with the exception of a null relationship between decentralization and formalization. Walton interpreted these results as indicating that dimensional models of organization structure inspired by Weber's bureaucratic ideal type retained relevance within the timeframe captured in his analysis and, by implication, despite the introduction of organizational innovations such as employee involvement, flexible work systems, and self-managing teams.

However, it is possible that the temporal span of Walton's meta-analysis failed to allow the time necessary for the full effects of these innovations to be realized. Walton estimated that 5 years passed between the collection of field data and publication of the resulting article on organization structure. If so, data for the final study included in his sample, published in 1997, were collected in 1992, prior to maturation of trends in the effects of the various organizational innovations (e.g., Castells, Reference Castells, Thornham, Bassett and Marris 2010 ; Knoke, Reference Knoke 2018 ; Paskvan & Kubicek, Reference Paskvan, Kubicek, Korunka and Kubicek 2017 ). Conceivably, the threats to bureaucratic organization associated with these innovations diminished the viability of bureaucratic dimensional models of organization structure in the years following Walton's study.

The following study addressed this possibility in a new meta-analysis of published research on dimensional models of organization structure that extended beyond Walton's sampling frame to include articles published between 1955, the earliest date of relevant dimensional research, and 2020, the final date of data collection for the new meta-analysis. In formulating the hypotheses for this meta-analysis, I chose to exclude horizontal differentiation for reasons indicated in the following method section. Consequently, my hypotheses and analyses examined five rather than six dimensions: formalization, standardization, specialization, decentralization, and vertical differentiation:

Hypothesis 1: The structural dimensions of formalization, standardization, specialization, decentralization, and vertical differentiation are positively intercorrelated in research published between 1955 and 1997.

Hypothesis 2: The structural dimensions of formalization, standardization, specialization, decentralization, and vertical differentiation are positively intercorrelated in research published between 1998 and 2020.

Hypothesis 3: For each pair of dimensions, comparison of intercorrelation between the two time periods will show a reduction in size of association.

Hypothesis 1 replicates Walton's primary hypothesis in order to verify that the present meta-analysis produced findings comparable to Walton's results. Hypothesis 2 is the same hypothesis extended to research published later than the studies included in Walton's sample, to examine whether Walton's findings generalize beyond the temporal scope of his study. Hypothesis 3 contrasts effect sizes between the two samples to reveal statistically significant differences over time and specifies the reduction in effect predicted by various organization theorists (e.g., Heydebrand, Reference Heydebrand 1989 ; Kanter, Reference Kanter 1989 ; Smith, Reference Smith 1997 ).

The meta-analysis reported in this article aggregated correlation statistics and corrected for sampling and measurement error using random-effects procedures developed by Schmidt and Hunter ( Reference Schmidt and Hunter 2015 ). To assemble the meta-analytic sample, three research associates and I began by searching the Web of Science and Google Scholar using the terms organization structure, organizational structure, bureaucracy, bureaucratic structure, formalization, standardization, centralization, decentralization, specialization, horizontal differentiation, and vertical differentiation. We chose to restrict sampling to published articles and book chapters, in contrast to the practice of including unpublished research. Our approach was consistent with the method used by Walton ( Reference Walton 2005 ) to collect his meta-analytic sample and also recognized the practical consideration that many researchers who had conducted early structure studies were no longer available to respond to requests for unpublished research. Including recent but not older unpublished research would have biased the sample selection process.

Our search extended from January 1955, to capture the earliest research that grounded Hall's ( Reference Hall 1963a ) founding model, to July 2020, the time of the final literature scan. My colleagues and I collected all publications identified in the search that conformed to the preceding sampling criteria, that contained correlations or transformable statistics pertaining to relationships between two or more of the five structural dimensions listed above, and that reported quantitative results. In addition, we collected review books, articles, and meta-analyses to serve as supplementary sources of search information (e.g., Donaldson, Reference Donaldson 2001 ; Gooding & Wagner, Reference Gooding and Wagner 1985 ; Miller, Reference Miller 1987 ; Mintzberg, Reference Mintzberg 1979 ; Scott, Reference Scott 1975 ; Walton, Reference Walton 2005 ). We then collected additional studies listed in the reference sections of the publications in hand, scanned their reference sections, and collected additional publications identified during the scan, and so forth, until no additional references were found.

An initial sample of 253 studies was obtained. Excluded prior to further analysis were studies that examined interpersonal ( n  = 22), group or team ( n  = 5), organizational subunit ( n  = 60), or inter-organizational ( n  = 10) structures to preserve a consistent level of analysis and theoretical explanation. This contrasts with Walton's ( Reference Walton 2005 ) approach, since 11 of the 64 studies included in his analysis were conducted at the department or subunit level. We also omitted one study (Ogidi, Reference Ogidi 2015 ) that reported exceptionally large correlations, in some cases more than two times larger than the next largest correlations for the same bivariate relationships, due to suspect data quality. A final collection of 155 publications yielded correlations or transformable statistics (e.g., t , χ 2 , d ; Wolf, Reference Wolf 1986 ). As indicated in Table 1 , publication activity captured by this collection rose to peaks of 10 and eight publications in 1973 and 1981, respectively, and declined gradually thereafter. Reference information for these publications is reported in Appendix 1.

Table 1. Sample description: studies published per year, 1963–2020

The earliest publication was Hall's ( Reference Hall 1963a ) study – earlier research identified in our search failed to report data on relevant relationships. Samples spanning multiple publications were consolidated to avoid duplication, and multiple samples from the same publication were coded separately. To ensure independence among observations, a necessary precondition for meta-analytic procedures, I averaged correlations from the same sample that captured multiple measures of the same variable to create a single correlation, resulting in a final sample of 346 correlations that pertained to bivariate relationships between the five structural dimensions.

Coding the sample of source correlations relied on matching the terminology, definitions, and operationalizations provided by publication authors with the definitions of structural dimensions indicated in this article. For example, correlations from the four original streams of research were coded as indicated in Table 2 . The three associates and I coded studies published prior to 1986 in an initial process of developing a coding sheet to be used to code all studies. We had 100% agreement on all coding except for coding on horizontal differentiation and specialization. Examination indicated that empirical definitions for the two dimensions shared substantial overlap since both tapped similar variation in the horizontal division of labor. In the end, we reached a complete agreement on a final coding sheet by including specialization in our study and excluding horizontal differentiation.

Table 2. Coding categories

Following inter-coder agreement on the coding sheet, I conducted all additional coding and analysis myself. To begin coding, I recoded all pre-1986 coding assignments to verify the accuracy of my use of the coding sheet. After confirmation that I was able to use the sheet without error, I coded the remaining studies (1986 and later) without assistance. Source correlations incorporating scales that differed in direction from other correlations measuring the same variable were reverse coded to ensure consistent directionality. For example, correlations including measures of centralization were reverse coded to create decentralization statistics.

I began the meta-analysis by subgrouping the coded source correlations by era of publication (1955–1997, 1998–2020). The breakpoint of 1997–1998 reflected the temporal endpoint of research published in Walton's ( Reference Walton 2005 ) meta-analytic sample and allowed comparisons between his sample and data published beyond the timeframe of Walton's investigation. I then performed a grand means analysis for the total sample of 346 source correlations after subgrouping into 1955–1997 and 1998–2020 era of publication subgroups. Then, to conduct tests of Hypotheses 1–3, I created two era of publication subgroups (1955–1997, 1998–2020) for each bivariate association among the five structural dimensions.

For each analysis, I calculated three sets of mean correlations and variance statistics to allow observation of the effects of error correction – a first set consisting of unadjusted means and variances, a second set of means weighted by sample size to adjust for sampling error, plus associated variances, and a third set of means adjusted for reliabilities in both covariates to correct for measurement error and then weighted by sample size to adjust for sampling error, plus related variances. In instances where source studies did not report reliability estimates I averaged reliability estimates from studies that used identical measures. If those were not available I used averaged estimates from similar measures. For objective measures (e.g., number of vertical layers, employee count, annual revenue) I used reliability estimates of .90 rather than the perfect (1.0) reliability often assumed in order to account for the effects of informant errors (e.g., provision of personal estimates rather than true counts, flawed counts due to recall or retrospect biases, perceptual lapses during data disclosure) and data management issues (e.g., coding and transcription errors, lost or missing data).

Schmidt and Hunter ( Reference Schmidt and Hunter 2015 ) also described a correction for range departure (whether restriction or attenuation), a source of error in which the variance among sample correlations diverges from the variance exhibited within the relevant reference population. Walton ( Reference Walton 2005 ) corrected for range restriction in his analysis but I chose to forego similar correction due to the absence of appropriate updated population information (e.g., indications of the full range of variation among organizations, surviving or not, pursuing varied purposes – businesses, government agencies, educational institutions, etc. – and located in countries throughout the world). Many current meta-analysts have used the same analytical strategy and have not included range departure corrections in their studies (e.g., Chamberlin, Newton, & LePine, Reference Chamberlin, Newton and LePine 2017 ; Hoch, Bommer, Dulebohn, & Wu, Reference Hoch, Bommer, Dulebohn and Wu 2018 ; Kurtessis, Eisenberger, Ford, Buffardi, Stewart, & Adis, Reference Kurtessis, Eisenberger, Ford, Buffardi, Stewart and Adis 2017 ).

Mean correlations adjusted for sampling and measurement error served as the focal statistics for assessment of the presence and degree of difference between subgroups. For each subgroup comparison, I also calculated 80% credibility intervals to assess within-subgroup heterogeneity indicative of possible moderator effects (Whitener, Reference Whitener 1990 ) and 95% confidence intervals to evaluate whether adjusted mean correlations differed from zero (Schmidt & Hunter, Reference Schmidt and Hunter 2015 ). Finally, I assessed the statistical significance of differences between pairs of 1955–1997 and 1998–2020 subgroup adjusted means with two-sample t approximations (Fisher, Reference Fisher 1935 ; Scheffé, Reference Scheffé 1970 ), a procedure described in Aguinis, Sturman, and Pierce ( Reference Aguinis, Sturman and Pierce 2008 ) and employed in other recent meta-analyses (e.g., Breuer, Huffmeier, & Hertel, Reference Breuer, Huffmeier and Hertel 2016 ; Jones, Sabat, King, Ahmad, McCausland, & Chen, Reference Jones, Sabat, King, Ahmad, McCausland and Chen 2017 ). I used the criterion statistic recommended by Cochran and Cox ( Reference Cochran and Cox 1957 ) to appraise t ’ test statistical significance.

Table 3 presents the meta-analysis' primary results. For each line in the table, K is the number of samples included in the subgroup indicated in the left-hand column, N is the total sample size of the K samples, ṝ is the unadjusted mean correlation for the subgroup, σ ṝ 2 is the variance among the source correlations included in the unadjusted mean, ṝ’ is the sample-size weighted mean correlation, σ ṝ’ 2 is the associated variance statistic, ṝ” is the reliability and sample-size adjusted mean correlation and σ ṝ” 2 is the related variance statistic, L and U are the lower and upper limits of the associated 80% credibility interval and 95% confidence interval, and t ’ is the approximate t test of the difference between the 1955–1997 and 1998–2020 adjusted mean correlations included in the bivariate relationship-time period block.

Table 3. Dimensional intercorrelations: primary analysis

** p  ≤ .01; * p  ≤ .05.

Reported first in the table is the grand means analysis that summarizes general tendencies in the meta-analytic sample. As indicated in the summary, 234 of the 346 correlations were from studies published between 1955 and 1997 and 112 were from studies published between 1998 and 2020. The adjusted mean correlation calculated for the 1955–1997 subsample was .24 and for the 1998–2020 was .04. A t ’-test of the difference between the subgroup means indicated that the difference was statistically significant ( t ’ = 6.59, p  ≤ .01).

Hypothesis 1 proposed that statistics from the time period sampled in Walton's meta-analysis would show evidence of positive relationships among the five structural dimensions, replicating Walton's results. Inspection of the 1955–1997 line in each bivariate block indicates that adjusted mean correlations were generally positive in direction and were often medium in size (Cohen, Reference Cohen 1988 ). With the exceptions of the adjusted mean correlations between formalization and decentralization (ṝ” = −.03, did not differ from .0) and standardization and decentralization (ṝ” = −.01, did not differ from .0), the results provided support for Hypothesis 1.

Hypothesis 2 posited that statistics from the time period following Walton's analysis would also show evidence of positive relationships among the five structural dimensions, extending Walton's findings into the present. Examination of the 1998–2020 line in each bivariate block indicated that two of the 10 possible adjusted mean correlations could not be calculated due to missing data (formalization with standardization, standardization with vertical differentiation). Four of the eight remaining adjusted means were nonzero and positive (formalization with specialization, ṝ” = .26; formalization with vertical differentiation, ṝ” = .15; standardization with specialization, ṝ” = .43; specialization with vertical differentiation, ṝ” = .16) supporting Hypothesis 2. However, the final four adjusted means were negative, in contrast to hypothesized expectations (formalization with decentralization, ṝ” = −.03; standardization with decentralization, ṝ” = −.31; specialization with decentralization, ṝ” = −.03; decentralization with vertical differentiation, ṝ” = −.20). Thus, findings related to Hypothesis 2 provided mixed support, with relationships involving decentralization serving as the source of all contrary results.

Hypothesis 3 predicted that comparisons between the adjusted mean correlations calculated for the two time periods within each bivariate block would show a reduction in size of association. Approximate t ’ tests shown in Table 1 's final column indicate the statistical significance of these comparisons. As reported in the column, missing data precluded the calculation of two t ’ statistics. For the remaining eight comparisons, five showed evidence of statistical significance and the 1998–2020 adjusted mean was the smaller of the two adjusted mean correlations (formalization with specialization, t ’ = 1.92, p   .05; formalization with vertical differentiation, t ’ = 3.58, p   .01; specialization with decentralization, t ’ = 4.72, p   .01; specialization with vertical differentiation, t ’ = 4.73, p   .01); and decentralization with vertical differentiation, t ” = 2.89, p   .01), consistent with Hypothesis 3. However, two comparisons failed to attain statistical significance (formalization with decentralization, t ’ = 1.01, n.s.; standardization with specialization, t ” = .77, n.s.) and the final comparison indicated that the 1998–2020 adjusted mean correlation for standardization with decentralization was larger than its 1955–1997 counterpart ( t ’ = 2.81, p   05). As summarized in Table 4 , for one dimension, standardization, missing data precluded comprehensive investigation. Among the remaining four dimensions, five of the six comparisons supported Hypothesis 3, indicating that relationships among formalization, specialization, decentralization, and vertical differentiation weakened appreciably between the two time periods contrasted in the study.

Table 4. Summary of meta-analytic comparisons, 1955–1997 with 1998–2020

a Result supports Hypothesis 3.

To test the robustness of these findings, I performed a series of moderator analyses to assess whether any might reveal specific conditions under which Hypotheses 2 and 3 would receive stronger support. As reported in Appendix 2, three of these analyses involved contrasts of manufacturing with other organization types (e.g., nonprofit service, governmental, educational, agricultural), institutional with questionnaire data collection methods, and data from the US, Canada, and Great Britain with data from all other locations. All three analyses failed to reveal findings that differed substantially from the results of the primary meta-analysis. In an additional two sensitivity analyses, also reported in Appendix 2, I reset the breakpoint between the two primary meta-analytic subgroupings from 1997–98 to 1989–90 and 2007–08. Again, results were consistent with the findings of the primary analysis

The meta-analysis reported in this article differed from Walton's meta-analysis in three notable respects. First, Walton's meta-analysis included six dimensions while the current meta-analysis examined five. The reason for this difference has already been indicated, and it seems unlikely that it affected the meta-analysis' general outcome in any significant way. Second, Walton's meta-analytic sample and the sample of pre-1998 publications analyzed in the present meta-analysis were not identical since, as previously indicated, Walton's sample included groups and teams, organizational departments, and inter-organizational networks while the present meta-analysis focused exclusively on organizations and did not include data from other levels of analysis. Third, Walton corrected the meta-analytic mean correlations in his study for range restriction whereas the analyses in the present meta-analysis did not. This difference is unlikely to have affected the results of my meta-analysis to a significant extent given that the range correction employed in Walton's study relied on data from reference populations that were themselves limited in range.

With these differences in mind, the present meta-analysis generally replicated the findings of Walton's ( Reference Walton 2005 ) meta-analysis regarding dimensional intercorrelation in data from studies published between 1955 and 1997. However, it showed an overall pattern of reduced intercorrelation in data from studies published between 1998 and 2020 and a decline in effect sizes between the two date-of-publication subgroups. To the degree that dimensional intercorrelation is considered a primary tenet of the Weber-inspired bureaucratic structural model that has grounded dimensional models of organization structure, the theoretical foundation of such models has weakened substantially since Walton's ( Reference Walton 2005 ) meta-analysis of structure research. Bureaucratic structural theory does not appear to be able to offer the conceptual underpinning for contemporary research that it was formerly capable of providing.

Research on structural dimensions requires a new theoretical foundation to motivate and support future studies. The search for this foundation requires, in turn, additional research. Where might this research begin? One answer to this question is implied in research reported by Puranam, Alexy, and Reitzig ( Reference Puranam, Alexy and Reitzig 2014 ), who sought to determine whether organization theory has lost its ability to explain new forms of organization or if instead it is still useful in understanding organizations and organizational processes. In case studies of Linux, Wikipedia, and Oticon, Puranam and colleagues discovered that existing theories provide meaningful insights into each organization's processes of task division and allocation, reward distribution, and information management, leading them to suggest that new forms of organization can be described as ‘novel bundles of old solutions.’ Their conclusion – that existing theory elucidates much of what initially appears novel because current-day solutions to problems of differentiation and integration tend to build on established practices rather than starting from scratch – suggests that discrete dimensions from existing structural models might characterize distinctive features of 21st century organization structures even if the bureaucratic structural model from which they originated is no longer explanatory. It follows that future research might focus on identifying new theoretical explanations for the effects of individual structural dimensions on one another and on other organizational features and processes.

A second path forward is suggested by theory and research that has identified a trend away from formalization and standardization toward other means of structural elaboration and coordination. For example, Zammuto et al. ( Reference Zammuto, Griffith, Majchrzak, Dougherty and Faraj 2007 ) and others (e.g., Galbraith, Reference Galbraith 2014 ; Porter & Heppelmann, Reference Porter and Heppelmann 2015 ) have described innovations in information technology that have transformed workplace practices by enabling widespread, synchronous information sharing to take place among interdependent parties, whether individuals and teams. Such information sharing allows individuals to communicate directly with one another without the intervention of structural intermediaries. It also enables teams to form communication linkages among their members and between themselves and other teams, creating horizontal connections that render hierarchical information management unnecessary. In this way, vertical differentiation, which would otherwise bridge horizontally adjacent teams, has become less essential as an information aggregation and distribution mechanism.

Advances in information technology also enable mass collaboration among otherwise unmanageable numbers of individuals and teams. This collaboration permits individuals and teams to visualize the entire work process, as opposed to the narrow segments otherwise accessible (Zammuto et al., Reference Zammuto, Griffith, Majchrzak, Dougherty and Faraj 2007 ). In turn, this visualization enables individuals and teams to enact performance innovations in real-time and without bureaucratic formalization since the individuals and teams engaged in performance have direct access to the information required to identify deficiencies and implement corrective modifications. The role of formalization as a means of creating collective rules and procedures is substantially reduced by the shared visualization enabled by information technology.

Mutual adjustment in a technology-mediated form is the process of horizontal information sharing described by Zammuto et al. ( Reference Zammuto, Griffith, Majchrzak, Dougherty and Faraj 2007 ) and others (e.g., Cascio & Montealegre, Reference Cascio and Montealegre 2016 ; Claggett & Karahanna, Reference Claggett and Karahanna 2018 ). It is a central element of employee involvement, flexible work systems, team self-management, and other new organizational practices identified as challenges to standardization, formalization, and bureaucratic organization (e.g., Palmer & Dunford, Reference Palmer and Dunford 2002 ; Smith, Reference Smith 1997 ). Whereas standardization is a process of coordination achieved by following plans (March & Simon, Reference March and Simon 1958 ; Mintzberg, Reference Mintzberg 1979 ), mutual adjustment consists of coordination achieved through processes of communication among interdependent parties that create activity synchronization and sustain common understanding (Lindblom, Reference Lindblom 1965 ; Mintzberg, Reference Mintzberg 1979 ; Thompson, Reference Thompson 1967 ). Standardization as a mechanism of structural linkage and coordination is supplemented or superseded by mutual adjustment among interdependent individuals and teams.

The rise of technology-assisted information sharing as a method of coordinating activities in new organization forms suggests the development of a theoretical model of organization structure built around the concept of mutual adjustment, both face-to-face and technologically mediated, as a primary means of enacting and coordinating structural relationships. Such development might follow the lead of founding structural studies and develop quantitative dimensions through deductive reasoning and large-sample field research. Dimensions assessing degrees of information technology saturation, visualization sharing, horizontal information distribution, and coordination by mutual adjustment all relate to structural coordination in the manner described above and are offered as examples to stimulate thinking beyond existing bureaucratic dimensions and models.

As a third alternative, it appears to be equally important that qualitative research be conducted to examine the developmental origins and processes of contemporary structures and structural dimensions. To illustrate what this research might look like, studies of the development of routines in organizations have focused on the emergence of recurrent procedures using a conceptual framework that balances structure with agency (Feldman & Pentland, Reference Feldman and Pentland 2003 ; Pentland, Feldman, Becker, & Liu, Reference Pentland, Feldman, Becker and Liu 2012 ). Qualitative analyses have examined improvisational processes that replace formalization in creating routines that function as standard procedures (e.g., Feldman, Reference Feldman 2000 ; Pentland & Rueter, Reference Pentland and Rueter 1994 ), and have described the emergence of specialization as interdependent parties routinize their work. Qualitative research's emphasis on process differs from the historical focus of structure studies on dimensional characterizations but has potential as a method of developing theoretical grounding for future dimensional research.

Dimensional models of organization structure inspired by Weber's bureaucratic ideal type were once a mainstay of organizational research, but the continued applicability of dimensional models is now questionable due to the emergence of new forms of organization unimagined during the earlier era of structure research. As these new forms have developed, structural dimensions that were formerly linked together both theoretically and empirically are now minimally related in many instances. Absent the theoretical grounding provided by Weber-inspired structural theory, structural dimensions no longer form a model but instead constitute a list without conceptual underpinning.

Organizations do have structures – enduring patterns of interdependence – and describing these structures using multidimensional characterizations remains essential. For managers, the importance of research aimed at the development of new structural dimensions and associated theoretical models might not seem readily apparent, but it is demonstrably so. Current-day managers lack the structural models required to provide meaningful advice in instances where they face the prospect of dealing with structural shortcomings. Application of existing models to diagnose and solve structural problems may prove helpful in those limited instances wherein discrete dimensions yield corrective advice. However, the days of meaningful multi-dimensional diagnoses are largely in the past. Practicing managers require dimensional models of organization structure that reflect the organization structures they manage, and this match requires that new streams of structure research be initiated and pursued.

In conclusion, dimensional models of structure published in organizational research were in many ways descriptive of mid-20th century organizations. It is now apparent, however, that dimensional models inspired by Weber's bureaucratic theory do not provide solid grounding for research on organization structure, necessitating a search for new conceptual foundations. This search offers the prospect of a renewed stream of investigations that will yield novel insights into the patterned regularity and ongoing coordination that are characterized in dimensional models of organization structure. The end goal of this article is to encourage and motivate this new structure research.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/jmo.2021.63 .

Acknowledgement

Thanks to Richard Z. Gooding, Aaron A. Buchko, and Timothy B. Palmer for their work in collecting and coding data analyzed in this article.

Wagner supplementary material

Appendices S1-S2

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The Effects of Organizational Structure on the Performance of Organizations

European Journal of Business and Innovation Research, Vol.5, No.6, pp.46-62, 2017

17 Pages Posted: 8 Jun 2021

Sunday C. Eze,

Landmark university - department of business studies, adenike o. bello, tolulope anthony adekola.

University of Queensland

Date Written: 2017

An organization can be likened to a building whose strength is determined by the structure and frames which holds it. The structure is the manner in which interrelated elements (resources) are arranged so that the building can be stable, resist stress and it provides the right form. To this end, for the performance of an organization to be effective, it is important to understand the right manner in which interrelated elements (structure) in the specific organization is arranged. To measure the performance of the organization, dependent variables such as sales, profit, and customer satisfaction will be considered. Also, the study utilized independent variables centralization and formalization organizational structures. This is to show the effects of the dependent variables on the independent variable. The research adopted quantitative design and applied mono method which brought about numerical data generated from questionnaire administered. The population of this study comprises of all staff of Covenant Micro Finance Bank as well as the customers of the banks. Total sum of 354 sample size comprising of both employees (51) and customers (303) of Covenant Micro Finance Bank is the sample size. The propositions assumed for this study are that: there is no relationship between organizational centralization and organizational customer satisfaction, there is no relationship between organizational centralization and organizational profit, there is no relationship between organizational formalization and organizational customer satisfaction and that there is no relationship between organizational formalization and organizational profit. Also, among the secondary data collected are views of various management researchers. As a result of the primary and secondary data collected, the study recommends that organizations should adopt decentralization structure and reduce formalization in the work place.

Keywords: organization, organizational performance, organizational structure, decentralization, formalization

Suggested Citation: Suggested Citation

Sunday C. Eze, (Contact Author)

University of queensland ( email ), do you have a job opening that you would like to promote on ssrn, paper statistics, related ejournals, organizations & markets: motivation & incentives ejournal.

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Volume 1, 1975, review article, organizational structure.

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• Vol. 1:1-20 (Volume publication date August 1975) https://doi.org/10.1146/annurev.so.01.080175.000245
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Organizational Structure, Page 1 of 1

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The Effects of Organizational Structure on the Performance of Organizations

() , , (), –

An organization can be likened to a building whose strength is determined by the structure and frames which holds it. The structure is the manner in which interrelated elements (resources) are arranged so that the building can be stable, resist stress and it provides the right form. To this end, for the performance of an organization to be effective, it is important to understand the right manner in which interrelated elements (structure) in the specific organization is arranged. To measure the performance of the organization, dependent variables such as sales, profit, and customer satisfaction will be considered. Also, the study utilized independent variables centralization and formalization organizational structures. This is to show the effects of the dependent variables on the independent variable. The research adopted quantitative design and applied mono method which brought about numerical data generated from questionnaire administered. The population of this study comprises of all staff of Covenant Micro Finance Bank as well as the customers of the banks. Total sum of 354 sample size comprising of both employees (51) and customers (303) of Covenant Micro Finance Bank is the sample size. The propositions assumed for this study are that: there is no relationship between organizational centralization and organizational customer satisfaction, there is no relationship between organizational centralization and organizational profit, there is no relationship between organizational formalization and organizational customer satisfaction and that there is no relationship between organizational formalization and organizational profit. Also, among the secondary data collected are views of various management researchers. As a result of the primary and secondary data collected, the study recommends that organizations should adopt decentralization structure and reduce formalization in the work place.

Keywords: Decentralization , Organization , Organizational Performance , Organizational structure , formalization.

This work by European American Journals is licensed under a  Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

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