Corporate distress and turnaround: integrating the literature and directing future research
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- Schweizer, L. & Nienhaus, A. Bus Res (2017). doi:10.1007/s40685-016-0041-8
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The topic of corporate distress and turnaround has been of interest to organizational change theory for many decades. This article considers existing reviews in discussing the current body of turnaround literature across multiple research fields and structures its work along a holistic framework. The numerous facets of corporate turnaround, resorting to general corporate restructuring research classifications, are clustered in a more detailed manner than those that merely rely on two commonly employed turnaround dimensions: “retrenchment” and “recovery.” The authors develop an agenda for future research based on this cross-disciplinary literature aggregation by highlighting current gaps and offering potential research questions. The review contributes to the understanding of corporate distress and turnaround by integrating different research streams. Additionally, the work emphasizes the need for further harmonization and operationalization in turnaround success metrics.
1 Corporate distress and turnaround: a review and research agenda
Corporate distress and turnaround has been a subject of research for many decades. Guiding conceptual works set the stage starting in the 1970s and early 1980s (Altman 1968; Bibeault 1982; Gordon 1971; Hambrick and Schecter 1983; Hofer 1980; Schendel and Patton 1976; Schendel et al. 1976). The 1979 Bankruptcy Reform Act and the related merger and acquisition wave in the 1980s amplified the number of bankruptcy filings during that time, thus increasing the topic’s relevance (Johnson 1996; Markides 1995). Early empirical works, such as studies by Robbins and Pearce (1992) or Pant (1991), offered the first insights into the turnaround wave of the 1980s.
Scholars from various fields have steadily enhanced our understanding of the topic based on this initial trend in publications, yielding many findings and definitions. Generally, turnaround can be defined as “a decline and recovery from distress” (Schendel et al. 1976). Grounded in the first conceptual discussions by Hofer (1980) or Bibeault (1982), corporate turnaround literature generally clusters organizational responses during distress as either “operational” or “strategic” in nature (Eichner 2010; Hambrick and Schecter 1983; Ofek 1993; Pearce and Robbins 1993; Schendel et al. 1976; Trahms et al. 2013). Although some works integrate such new facets as different process stages (Chowdhury 2002) or contextual interdependencies (Castrogiovanni and Bruton 2000), corporate turnaround research seems to adhere to this dichotomous categorization of organizational change. The initial reviews by Pearce and Robbins (1993) and Pandit (2000) reinforce this concept, and even more recent works sort these findings accordingly, such as the overview presented by Trahms et al. (2013).
However, as firms fighting for survival are confronted with the need for comprehensive organizational change, possible turnaround strategies are manifold and fundamentally differ in their nature or theoretical grounding (Bowman and Singh 1993; Ndofor et al. 2013). Hence, reviewing works from the corporate distress and turnaround field from the perspective of only two dimensions might lead to spurious conclusions. For instance, as Loui and Smith (2006) confirm, empirical findings regarding the efficiency of top management replacements as a turnaround strategy seem contradictive when neglecting procedural and contextual influences. However, in considering the timing and the process stage of CEOs’ dismissal, it becomes clear that only executive replacements initiated during the early stages of distress positively affect turnaround (Daily and Dalton 1995; Tushman and Rosenkopf 1996). Conversely, following the concept of organizational inertia, installing new management after distress has prevailed for several years, resulting in a diminished ability to react and lower turnaround probabilities. Although prior reviews already provide an overview of selected publications on the matter, they fall short in comprehensively clustering the investigated turnaround strategies and do not account for the many facets of potential crisis responses as well as different research fields’ corresponding foci regarding corporate turnaround. No study to our knowledge accounts for all turnaround literature, encompassing content, process, and context dimensions across multiple research fields. We resort to a more detailed conceptual organizational change framework to close this gap and overcome the shortcomings of a merely dichotomous classification of turnaround. Although some turnaround frameworks incorporate such different contextual settings as exogenous or internal causes for decline (Tushman and Rosenkopf 1996), or consider different process stages (Barker and Duhaime 1997), the interdependencies between process, context, and the chosen turnaround strategy have been neglected. However, considering the underlying context and timing helps avoid misinterpretation when comparing different turnaround decisions (Pettigrew 2012).
The work at hand offers four additional contributions, and especially when compared to Trahms et al.’s (2013) most recent review. First, we integrate findings from the general management field with studies from accounting, economics, sociology, and especially finance. Trahms et al. (2013) based their review and research agenda on 40 articles from eight general management journals; however, our analysis comprises 276 works from 25 journals, spanning across the five research fields. Second, by resorting to different research fields, like. finance, we can discuss additional turnaround measures. While Trahms et al. (2013) focused on response factors related to managerial cognition, strategic leadership, and stakeholder management, our review additionally discusses the effects of such finance-related turnaround moves as debt restructuring. Third, Trahms et al. (2013) base their research agenda on, and limit it to, resource orchestration, strategic leadership, and stakeholder management. This paper’s research agenda, in contrast, encompasses considerably more research areas, attempting to reflect potential research opportunities along all dimensions of its framework. Fourth, we adopt Trahms et al.’s (2013) discussion regarding turnaround outcomes. Our argument parallels that of Haleblian et al. (2009) in the field of mergers and acquisitions (M&A), as we demonstrate current shortcomings regarding the operationalization of success measures. Although Trahms et al. (2013) already offer a more detailed metric with seven different turnaround outcomes, their operationalization remains unclear. We resort to definitions from other research fields, namely finance and M&A, to contribute to this discussion and fill the remaining white spots.
Thus, this work provides a comprehensive overview of the status quo on turnaround research, integrating findings from relevant research streams and theoretical lenses. This article contributes to corporate turnaround research as a part of the organizational change theory as the first to consolidate and structure over 260 relevant publications according to a holistic framework, further detailing operational and strategic turnaround. We account for the different facets of content, process, and context research to bridge the gap between mostly detached substreams. Further, the review focuses on the meta-topic of measuring corporate turnaround success and aims to provide a basis for the prospective second “high tide” of turnaround research, most likely resulting from the recent global financial crises. The study summarizes the last decades of relevant research, builds on existing reviews on the matter, pinpoints still unsolved and contradicting topics, identifies important gaps, and defines an agenda for future research.
We adapt Brauer’s (2006) and Haleblian et al.’s (2009) approaches to reviewing literature by following a six-step approach of identifying, reviewing, and classifying relevant work. First, by defining a review period from 1992 to 2013, we ensured the inclusion of all publications of the first “high tide” of turnaround literature resulting from the M&A wave in the 1980s until 2013. Second, we identified five research areas to focus our search, namely, management, finance, economics, accounting, and sociology (Brauer 2006). Third, we conducted a keyword search using the aforementioned constraints, employing EBSCO and JSTOR databases as well as the Social Science Research Network. We accounted for a possible publication bias by screening Google Scholar for relevant working papers as well as unpublished works. The keywords spanned bankrupt*, crisis, decline, default, distress*, survival, and turnaround. As the employed framework resorts to concepts of general organizational change, divest*, reorganization, and restruct* were checked as additional keywords. Fourth, a manual search by issue of the top 25 peer-reviewed journals over the defined period yielded additional publications.1 Fifth, we identified ground-setting works prior to 1992 by employing an ancestry search within the key papers. This assured the inclusion of publications leading back to Altman (1968), who provided one of the first bankruptcy prediction models that still lays the foundation for numerous works in this field (Chava and Jarrow 2004; Ohlson 1980; Shumway 2001; Zmijewski 1984). The initial five steps yielded 1040 articles generally related to the research topic. These 1040 works were screened in more detail, in a sixth and final step before coding, and were prioritized according to relevance. This resulted in a sample of 276 papers.
The mean sample length is 11.59 years. Amburgey et al. (1993) study of the Finish newspaper industry represents a clear outlier, with a sample length of 192 years, ranging from 1771 to 1963 and representing 1011 firms. The same can be noted in the works of Kronborg and Thomsen (2009) as well as Tripsas (1997); the first analyzes the survival of Danish corporations over the course of 110 years, and the latter discusses technological changes in the US typesetting industry over 104 years. The mean sample size is 536.02, with the vast majority using firm-level data. Figure 2 depicts the distributions of sample size, length, and publication lag.
Of the publications that disclose their sample characteristics, 154 studies have samples solely based in the USA, followed by 36 works analyzing European markets, of which the UK represents the majority, with 14 single-country studies. This is followed by six German and three Swedish samples. Asia accounts for a total of 14 studies, focusing primarily on Japan (6 publications). Only ten articles handle samples of more than ten countries (Acharya and Subramanian 2009; Atanassov and Kim 2009; Faccio et al. 2006; Lel and Miller 2008; Lin et al. 2006; Lins et al. 2013; McDonald and Westphal 2003; Sarkar et al. 2006; Tong and Wei 2011; van Witteloostuijn 1998). The overall distribution of regional focus indicates a clear Anglo-American bias of empirical research on the topic, independent of the research field.
2 The framework of corporate turnaround
The theoretical framework is developed based on organizational change theory, which can generally be divided into content, process, and context research. This yields a holistic framework, with the “what” of change summarized under content, the “why” of change defined as inner and outer context, and the “how” accounting for the organizational change process (Armenakis and Bedeian 1999; Castrogiovanni and Bruton 2000; Pettigrew 1987). The framework accounts for the many success measures employed across different research fields with an outcome dimension, which provides a basis for an effective consolidation of the empirical results generated by different research fields.
Based on organizational theory, content research analyzes the different strategies and activities conducted during turnaround. The taxonomy of content is further detailed based on dimensions common to corporate restructuring research to partially account for the severely differing natures of actions. Hence, classifications are made according to “portfolio restructuring,” “financial restructuring,” and “operational restructuring” (Eichner 2010). Portfolio restructuring can be understood as a severe change in a firm’s asset structure, by either investing or divesting in divisions, plants, and business units (Bowman and Singh 1993). Financial restructuring includes alterations of a firm’s capital structure and financing behavior (Sudarsanam and Lai 2001). As operational restructuring still serves as an umbrella for a myriad of activities targeting efficiency enhancements, more recent publications suggest a detached category, including forced managerial and top management team replacements (Eichner 2010; Sudarsanam and Lai 2001). Although some categories are based on corporate restructuring research, they are equally important for turnaround during organizational distress, as successfully avoiding default inevitably incorporates far-reaching change (Eichner 2010).
Publications analyzing the different turnaround stages and timing are summarized under the framework’s process dimension. However, the sequencing has not been consistently institutionalized within turnaround research until now. Robbins and Pearce (1993) adapt Bibeault’s (1982) five-step approach and define four steps, which began with the turnaround situation, retrenchment response, recovery response, and turnaround success, with the retrenchment and recovery phases as the relevant implementation phases (Eichner 2010). Filatotchev and Toms (2006) extend this two-stage turnaround with a “realignment” stage. Pearce (2007) offers another definition, with a three-phase model including “decline,” “redirection,” and “reestablishment.” Consequently, Smith and Graves (2005) illustrate the lack of consensus between researchers regarding what constitutes a turnaround situation, or turnaround success, with respect to timing. As the framework used in the article at hand focuses on turnaround strategies’ implementation, the process dimension is subdivided into “retrenchment” and “recovery” (Barker and Duhaime 1997). The former comprised decline-stemming strategies to impede or even reverse decline”, and the latter encompasses growth-oriented strategies that target profitability and sustainable growth (Arogyaswamy et al. 1995; Freeman and Cameron 1993; Robbins and Pearce 1992).
Although Bibeault (1982) initially stated that turnaround time is a function of the organization’s size, thus linking process to context, Hoffman (1989) postulates that only 2 of the 17 studies investigated in his paper analyze whether the causes were statistically associated with downturn. This is unexpected, as numerous influential works state the importance of considering the root cause when determining the reaction to decline (Castrogiovanni and Bruton 2000; Hofer 1980; Pearce and Michael 2006; Schendel et al. 1976). However, both the initial cause of decline, as argued by Hofer (1980), and internal organizational and external environmental factors, such as the stage in the product’s life cycle, competitive position, and industry type, must be addressed (O’Neill 1986).
3 Turnaround content
The myriad of strategies related to a firm’s survival can be clustered into four categories: operational, managerial, portfolio, and financial restructuring. Each category offers numerous subsets of turnaround moves (Lai and Sudarsanam 1997).
3.1 Operational restructuring
Operational restructuring focuses on operating efficiency that does not target corporate strategy. In the context of corporate distress, operating actions refer to “doing things right”, whereas strategic moves can be classified as “doing the right things” (Hofer 1980). However, not all actions undertaken are observable for researchers (Eichner 2010). For instance, the interdependencies between individual actions significantly contribute to variance explanations in operating performance, but are hardly visible (Yawson 2005, 2009). This may offer a feasible explanation for mixed results, despite the broad conceptual support (Holder-Webb et al. 2005).
Over 40% of firms that file for Chapter 11 experience operating losses in the 3 years following bankruptcy, with one-third reentering bankruptcy or private debt restructuring (Hotchkiss 1995). This yields less than 10% successful turnaround cases (Moulton and Thomas 1993). The fact that a majority of firms undertaking operational restructuring efforts require further restructuring indicates a potential bias toward unprofitable firms’ continuation (Acharya et al. 2007; Hotchkiss 1995; Routledge and Gadenne 2000). An explanation lies within the technicalities of bankruptcy law in the USA. As an inefficient firm that files for Chapter 11 bankruptcy is allowed to continue operating in the same line of obviously unprofitable business before liquidation, operational and thus nonstrategic reorganization is offered to the firm as an alternative to potential default (Campbell 1996; White 1989); both equity holders and creditors prefer this unnatural closing alternative. The former favor continuation to preserve their interests in the company, while the latter calculate the potential future returns versus liquidation outcomes (Routledge and Gadenne 2000). Hence, as Azoulay and Shane (2001) conclude, a firm’s choice regarding continuation is largely influenced by stakeholders’ contractual frameworks and emphasizes the importance of accounting for institutional context in turnaround research.
The partially contradictory results indicate the need to analyze the myriad of operational restructuring moves in more detailed subgroups. Four exhaustive subcategories are deployed to account for the breadth of potential operational restructuring moves, allowing for both efficiency-oriented and growth-fostering actions. Operational restructuring moves, based on Sudarsanam and Lai’s (2001) operational restructuring classifications, can either alter an organization’s existing processes, adjust product and service offerings as well as related sales activities, or address changes in operating assets or underlying capital structures (Sudarsanam and Lai 2001). Further, as reducing staff might significantly contribute to efficiency improvements or cost reductions, another important subcategory consists of operational restructuring moves that address a firm’s human capital. These subcategories clearly differ from more strategically oriented moves, for instance the organizational restructuring as summarized by Bowman and Singh (1993), which includes more severe measures, such as acquisitions.
3.1.1 Organizational processes
Although conceptual works identify organizational process changes as a key element of operational turnaround, this has been largely neglected in empirical studies, primarily due to the difficulties in observing and quantifying process alterations from an external perspective. Altering production processes proved to be an effective instrument when facing corporate decline, and especially under the contingency of environmental changes (Robins 1993). However, not all processes are retrenchment oriented; Cefis and Marsili (2005) emphasize that growth-oriented process innovations particularly have a strong effect on survival chances. Early implementation is critical to account for a potential lag regarding process renewal and turnaround effects (Sinha and Noble 2008). Thus, organizational process restructuring is most effective when implemented during the retrenchment phase of corporate turnaround, even when defined as stabilizing and growth oriented (Eichner 2010). Longitudinal research and the deployment of survey techniques in future studies could add empirical evidence to existing conceptual works and thus address the difficulties in observability and external measurement (Bititci et al. 2012). Further examples include DeWitt et al.’s (1998) study, which analyzes feedback from 699 employee surveys, or Elliott and Smith’s (2006) survey-based investigation of crisis situations in the UK’s soccer industry.
3.1.2 Product and sales
The likelihood of corporate default depends on the product’s life cycle stage, primarily explained by continuous technological advancements and intensifying competition among mature products (Agarwal and Gort 2002; Agarwal et al. 2002). An overly specialized product offering can cause or accelerate corporate distress (Opler and Titman 1994). Thus, the improvement of product propositions through variety enhancements or innovation significantly fosters survival chances. However, Cottrell and Nault (2004) find that pure extensions to existing products are counterproductive, and even hinder operating performance. Therefore, innovation plays a critical role during corporate distress, enabling firms to charge an innovation premium (Cefis and Marsili 2005; Ketchen and Palmer 1999).
3.1.3 Human capital
Management literature provides a majority of work on human capital strategies within turnaround research (McKinley 1993). Numerous studies and full reviews have been recently published regarding various subjects including downsizing, such as Datta et al.’s (2010) extensive review. However, not all works directly relate to a distinct organizational turnaround context. For instance, Wayhan and Werner (2000) demonstrate the positive effect of layoffs on subsequent financial performance, independent of the company’s current health. Hence, downsizing studies’ results must be compared with caution when analyzing their effects on turnaround outcome. Additional alternatives to address default include pure workforce reduction to increase the revenue per employee and decrease costs, as well as resorting to low-cost country workers or introducing flexible employment models (Taplin and Winterton 1995).
Organizational change theory demonstrates the conflict that lays the foundation for employee downsizing literature during corporate distress: while such organizational factors as distress yield a need to lay off employees, institutional context factors, such as governments, unions, or domestic ownership, create social and institutional pressures that hinder downsizing (Alakent and Lee 2010; Shane and Foo 1999). An additional challenge arises from the difficulty in operationalizing employee downsizing (Datta et al. 2010). Many scholars reference an individually defined percentage of a reduction in overall headcount as a threshold for human capital restructuring (Datta et al. 2010; Eichner 2010).
Consequently, studies on workforce restructuring during corporate distress offer contradictory results. John et al. (1992) and Chowdhury and Lang (1996) state that layoffs are the largest contributors to cost savings during the course of operational restructuring and significantly increase the likelihood of survival. However, downsizing used as an ad hoc measure solely to reduce costs may hinder the full potential of human capital restructuring, regardless of its use as a measure to increase efficiency, or as a turnaround move (Freeman and Cameron 1993). Nevertheless, downsizing is often used in an attempt to immediately reduce costs and regain liquidity (Budros 1999; Folger and Skarlicki 1998; Norman et al. 2013). Although spontaneous layoffs during retrenchment may decrease costs in the short term, downsizing is more effective when used during the recovery and stabilization phase of a turnaround (Love and Nohria 2005).
Conversely, many studies underpin downsizing’s possible negative effects; for instance, it might decrease creativity among employees and negatively impacts survivors’ commitment, known as “survivorship syndrome” (Amabile and Conti 1999; Brockner et al. 2004). Further, downsizing negatively affects firm reputation from an institutional perspective (Flanagan and O’Shaughnessy 2005; Love and Kraatz 2009). These negative implications are more severe with high research and development and capital intensities, or if a recession prevails (Guthrie and Datta 2008; Lin et al. 2008). Nixon et al. (2004) and Hannan et al. (2006) state that downsizing negatively affects market returns, as explained by the significant loss of intellectual capital.
However, these risks are moderated by the implementation process and overall turnaround context. For instance, Martin et al. (1995) find that employee commitment is significantly enhanced when the staff is involved during downsizing. Outplacement programs and ensuring objectivity and ethical procedures additionally foster commitment (DeWitt 1998; DeWitt et al. 1998; Elliott and Smith 2006; Love and Nohria 2005; Ludwig 1993; Nixon et al. 2004). This can subsequently trigger positive financial performance after layoffs (Chadwick et al. 2004; Reilly et al. 1993; Trevor and Nyberg 2008).
3.1.4 Capital expenditures
Within the boundaries of operational restructuring during corporate distress, capital expenditure (CAPEX) alterations enhance operating efficiency with existing resources and do not include fundamental strategic changes in assets that are summarized under portfolio restructuring.
CAPEX changes are relatively easy to implement and often demonstrate direct results, as short-term budget allocations can be employed as a primary lever to control expenditures. Consequently, operational restructuring is twofold through CAPEX alterations (Eichner 2010). During the retrenchment phase, CAPEX reductions can effectively lessen financial tightening, and during the stabilization phase, CAPEX increases rejuvenate assets’ productivity (Schendel et al. 1976). However, empirical results remain inconclusive; Andrade and Kaplan (1998) state that CAPEX reductions are inevitable for firms in distress, and Sudarsanam and Lai (2001) cannot find any significant influence. Moreover, Furrer et al. (2007) postulate that CAPEX negatively relates to market performance in the years immediately after a turnaround, and only reveals positive effects in subsequent mid-term years. Hence, significant performance enhancement can be expected only if accompanied by strategic asset retrenchment or portfolio restructuring (Lins et al. 2013; Pearce and Robbins 1993). Further, firms in distress often cannot increase CAPEX due to immediate cash flow constraints. During the 2008 financial crisis, 86% of CFOs in a sample of distressed US firms declared an inability to invest in attractive projects due to financial constraints (Campello et al. 2010). Thus, as D’Aveni (1989) summarizes, reductions in CAPEX alone may buy time, but do not securely ensure turnaround.
3.2 Management replacements
The theoretical foundation of CEO replacement is linked to agency theory, which analyzes the alignment of interests between top management as agents, and stockholders and creditors as principals (Barker et al. 2001).
3.2.1 CEO exchange
From a behavioral theory perspective, CEO dismissal during corporate distress circumvents a “threat-rigidity response” in the face of distress (Daily and Dalton 1995; Tushman and Rosenkopf 1996). Strategy innovation is a critical success factor during turnaround, highly dependent on the CEO’s intrinsic beliefs in this opportunity, thus making a change in leadership inevitable (Stopford and Baden-Fuller 1990).
Consequently, researchers initially conceptualized CEO replacement as an integral part of every turnaround effort (Bibeault 1982; Boeker 1997; Hofer 1980). The ability to make critical choices implies an overidentification risk regarding the organization and its current strategy; this makes organizational failure a personal defeat, escalating a commitment to a failing strategy (Clapham et al. 2005). Accordingly, Whitaker (1999) states that more firms enter financial distress as a result of mismanagement than economic distress.
Nevertheless, agency costs can also be reduced by aligning management action with shareholder interests by significantly reducing the income of CEOs who remain in the distressed firm (Gilson and Vetsuypens 1993). Thus, manager replacement is a common, but unessential element of a successful turnaround (Clapham et al. 2005; Mackey 2008). Gilson and Vetsuypens (1993) report that 33% of all CEOs are replaced during turnaround efforts. However, legal contingencies must be accounted for.
Barker et al. (2001) conclude that little systematic evidence exists to prove that replacements lead to organizational change during corporate distress. Chen and Hambrick (2012) and Daily and Dalton (1995) posit that CEO replacement has no effect on turnaround likelihood. Unless the preceding share performance is extremely good or bad, CEO replacement seems to have no significant explanatory power (Warner et al. 1988). These findings might be an effect of firms’ late reaction to facing default. While decline can be detected as early as 10 years prior to bankruptcy, management is not replaced until immediate corporate distress (Hambrick and D’Aveni 1992). As a consequence, it becomes increasingly difficult to save the already half-sunken ship.
However, Elloumi and Gueyié (2001) contradict this, suggesting that the composition of human capital explains distress beyond an exclusive reliance on financial indicators. Furthermore, event studies by Weisbach (1988) and Davidson et al. (1993) support positive stock price reactions on days when resignations are announced. Bankruptcy law in the USA allows for the incumbent’s continued engagement, while Swedish bankruptcy filings automatically terminate the CEO’s employment and yield the firm’s auction. Thus, differences in institutional contexts lead to diverse conclusions regarding exchanges in top management (Espen and Thorburn 2003, 2008).
However, these inconclusive results cannot be solely attributed to legal contingencies. Various scholars empirically support management replacements by stating that a CEO’s forced resignation is preceded by significant declines in operating performance and is followed by substantial performance improvements (Denis and Denis 1995b; Yawson 2009). Newer studies examine not only the CEO’s disengagement, but also the relationship between the ex-leader and the firm. The findings underpin the need for a clear-cut: if the fired CEO remains as a member of the board, the successor cannot implement true strategic change (Filatotchev et al. 2000; Quigley and Hambrick 2012).
3.2.2 Top management team exchange
Limiting analyses to CEOs will not fully capture management succession’s impact on performance (Lohrke et al. 2004; Shen and Cannella 2002). Siggelkow and Rivkin (2005) argue that the second hierarchy level’s power must not be underestimated. Mueller and Barker (1997) support this by discovering a significant negative relationship between the proportions of pre-decline top managers remaining in the firm and turnaround.
Some scholars question management replacements in principle, as terminated managers experience significant personal costs after forced replacement (e.g., no employment in listed firms for at least 3 years). Thus, a distressed firm’s managers have incentives to increase performance (Espen and Thorburn 2003; Gilson 1989).
Moreover, newer work more closely examines the possible influences of contingency effects. The root cause of corporate decline might significantly moderate the stock market performance effects from management replacement. On the one hand, management retention yields credibility and, thus, positive market returns during uncontrollable external causes, such as political changes or industry decline (Eisfeldt and Kuhnen 2013). On the other hand, the effect of CEO replacement as a reaction to internal turmoil is moderated by various effects and is not directly linked to performance (Dowell et al. 2011; Fredrickson et al. 1988).
3.2.3 Board of directors
Studies on corporate governance might further explain the inconclusive results on managerial replacements (Westphal and Bednar 2005). Inside directors strongly depend on the CEO, whereas external directors can initiate turnaround activities when other governance mechanisms fail (Daily 1996; Johnson et al. 1993). Further, outsiders increase the board’s diversity (Filatotchev and Toms 2003). They can provide additional expertise, regaining trust of creditors and shareholders (Daily 1996). Multiple studies offer empirical evidence by depicting a strong correlation between the number of outside directors and survival chances (Barker et al. 2001; Daily 1995; Daily and Dalton 1994a; Hoskisson et al. 1994; Mueller and Barker 1997). However, various works contradict this by reporting that bankrupt firms do not have fewer independent directors than surviving firms (Daily and Dalton 1994b; Elloumi and Gueyié 2001).
Blockholders further extend this framework by significantly influencing management replacements’ effectiveness by increasing the likelihood of CEO turnover. Hence, surviving companies tend to have larger institutional investors (Filatotchev and Toms 2003; Kang and Shivdasani 1997). However, Jostarndt and Sautner (2008) cannot find a correlation between ownership concentration and managerial replacement likelihood during distress.
A different research strand argues that top managers’ personal characteristics have the greatest impact on managerial replacement success during distress (Boeker 1997; Hall 1994; Ling et al. 2007). Chen and Hambrick (2012) state that merely firing the CEO does not guarantee turnaround; rather, the key determinant is the installation of a leader with attributes more suited to successfully develop and implement turnaround strategies. Firms that are less prone to experiencing corporate default have top management teams with higher functional heterogeneity and education levels, shorter organizational tenures, and more tenure heterogeneity (Greening and Johnson 1996; Hall 1994). Further, CEOs with high opportunity costs are more likely to assume higher risks and more rapidly fail (Arora and Nandkumar 2011). Additionally, a CEO’s social network ties determine his response to decline due to a herding bias (McDonald and Westphal 2003). Celebrity CEOs tend to produce excess stakeholder expectations, subsequently leading to failure (Sinha et al. 2012).
Further, more positive market returns are achieved for external successors than internal ones, and especially after bankruptcy (Davidson et al. 1993). However, these results seem to be limited to the private sector, as Boyne and Meier (2009) find that turnaround is more likely to be achieved by insiders than outsiders in the context of superintendent exchange in declining school districts. Additionally, Hannan et al. (2006) and Khanna and Poulsen (1995) find no positive correlation between the appointment of outside successors and survival likelihood.
The mixed effects of management’s replacement during distress lead to the conclusion that they are heavily contingent on contextual factors. The high rate of CEO exchange during distress contrasts with only a partially positive impact and draws the assumption that managers often serve as scapegoats, without actual accountability (Iqbal and French 2005; Khanna and Poulsen 1995).
3.3 Portfolio restructuring
Portfolio restructuring contrasts operational restructuring by focusing on a strategically motivated alteration of a company’s portfolio. While the first targets liquidity or efficiency improvements, the latter aims to refocus the business. Corporate distress researchers agree that refocus is an integral component during turnaround (Gibbs 1993; Hoskisson et al. 2004; Lasfer et al. 1996; O’Neill 1986). From an agency perspective, portfolio restructuring reduces information asymmetries between equity holders and managers by transferring assets to the capital market (Bergh et al. 2008; Gibbs 1993; Li 2013).
Hoskisson et al. (2004) indicate that a reorientation toward a peer group of businesses enables the distressed firm to access additional resources and soften potential harm from intensified competition or legislative changes. However, if the portfolio restructuring moves are too broad, their impact on performance diminishes (Brauer 2006). Greening and Johnson (1996) state that firms with top management’s energy and attention solely concentrated on managing a complex, excessively diverse portfolio restructuring may lack the time to handle daily business, thus increasing the likelihood of default.
Empirical evidence based on broad conceptual support is strong. For instance, refocusing announcements are associated with significant positive market reactions after performance declines (Denis and Kruse 2000; Markides 1992), as markets interpret the refocusing as a step toward reducing financial distress costs (Berger and Ofek 1999; Lasfer et al. 1996). However, if corporate decline is already critical, increasing financial constraints might decrease the ability to act (Dawley et al. 2002).
Cost retrenchment under operational restructuring has only limited influence, and is often insufficient to achieve turnaround alone. A significant increase in the likelihood of survival is probable only in combination with strategic asset retrenchment, as pre-distress diversification levels are often too high (Asquith et al. 1994; Denis and Rodgers 2007; Li and Tallman 2011; Markides 1992; Robbins and Pearce 1992). This positive effect is primarily due to reduced leverage and an increased focus on core competencies, as well as the productivity growth achieved by divestitures of less productive plants (Denis and Kruse 2000; Denis and Shome 2005; Hakkala 2006; Markides 1995). Nevertheless, empirical analyses by Lamont et al. (1994) suggest that excessively rigorous divestment can hinder recovery.
Although Cusatis et al. (1993) support portfolio restructuring’s positive effects by finding positive and abnormal returns, Winn (1997) states that strategic asset reduction does not turn around asset productivity, as highly distressed firms often sell off their most lucrative and often strategically important assets below value to increase cash (Andrade and Kaplan 1998; Campello et al. 2010). Additionally, markets might negatively react as a substantial power shift occurs during corporate distress, from equity holders to creditors (Li 2013). Thus, creditors influence divestiture decisions and obtain the majority of asset sale proceedings instead of reinvesting them into the firm. Thus, investors’ return on assets diminishes (Brown et al. 1993). Brauer (2006) has more extensively reviewed divestures in his work titled: “What Have We Acquired and What Should We Acquire in Divestiture Research? A Review and Research Agenda.”
A sole focus on decreases in assets leads to a one-sided strategy that lacks sufficient leverage and makes the firm more prone to crises (Sheaffer and Mano-Negrin 2003). Dahiya et al. (2003) highlight the possibility of debtor-in-possession financing. This type of secured financing for firms under Chapter 11 bankruptcy enables investments, thus increasing firms’ chances for survival. Acquiring new resources positively affects firms’ recovery (Morrow et al. 2007; Smith and Graves 2005; Wu 2013). However, the positive effect is limited to true investments. Refocusing strategies that contain only alliances or joint ventures are not found to yield positive returns (Morrow et al. 2007). Furthermore, Wan and Yiu (2009) note that acquisitions are the most effective during environmental turmoil, with only limited effects in stable contexts.
3.4 Financial restructuring
One primary contribution of the review at hand is the consideration of various research fields. This review employs a broad definition to capture the entire breadth of research on financial restructuring during turnaround, including all alterations of a firm’s capital structure. Possible alterations in a turnaround context can be generally classified as having objectives of either debt restructuring or liquidity improvement (John 1993). Liquidity improvements include working capital optimization, dividend cuts, or equity issuance, but debt restructuring comprises debt provisions, reduction, and structural changes, as well as balance sheet cleanups (Eichner 2010; Opler 1993). Working capital restructuring does not include alterations of production processes, included in operational restructuring, to ensure conceptual rigor. Hence, primary levers of this type of financial restructuring in the context of corporate distress include inventory management, stretching payables, and optimizing receivables (Eichner 2010).
The costs of distress are significant from a financial perspective; thus, corporations are motivated to avoid bankruptcy filings through private financial reorganization (Franks and Torous 1994). Although the actual amount of financial distress cost varies, scholars agree on its significance and impact on the likelihood of turnaround. Wruck (1990) reports an average direct distress cost of 3.5% of market value and indirect costs of 9–15%. Andrade and Kaplan (1998) find slightly higher distress costs of 10% to 20% for US firms, and Almeida and Philippon (2007) calculate a net present value of distress of 4.5% of pre-distress value. Gilson et al. (1990) find that 50% of distressed firms successfully employ private financial restructuring during distress. Franks and Torous (1994) state that creditors’ recovery rates are significantly higher under private reorganization than during bankruptcy filings. However, firms with potentially higher bankruptcy costs, such as small firms or those with low asset tangibility, are biased toward choosing capital structures with higher inherent bankruptcy risks (Hovakimian et al. 2012). Nevertheless, Bowman et al. (1999) note that financial restructuring is the most effective means of achieving turnaround. Moreover, Yawson (2005) compares financial restructuring to other instruments to emphasize financial reorganization’s immediate effects, compared to portfolio restructuring’s lagged impacts on performance.
3.4.1 Debt restructuring
Finance theorists argue that overleverage is commonly a primary cause of distress (Molina 2005). Equity allows a firm to share aggregate risks with creditors, minimizing the vulnerability in distress during downturns (Gertler and Hubbard 1993). However, this tax shield creates a bias against equity (Asquith et al. 1994; Berk et al. 2010). Thus, and as Wruck (1990) summarizes, a reduction in leverage avoids distress, but does not maximize value. This is especially the case when considering Elkamhi et al.’s (2012) findings, which state that these costs cannot offset the tax shield of debt.
Nevertheless, numerous works underpin the positive effects of leverage reduction (Kahl 2002; Lin et al. 2008; Opler and Titman 1994; Sheppard 1994). Zingales (1998) argues that high leverage reduces survival chances by curtailing investments, and Giroud et al. (2012) find significant performance improvements after debt reductions. However, Winn (1997) contradicts these findings and does not find any asset productivity growth due to debt reduction during turnaround. Kalay et al. (2007) further state that firms with higher debt ratios experience greater operating performance improvements. Consequently, George and Hwang (2010) and Routledge and Gadenne (2000) conclude that companies experiencing successful turnaround are more highly leveraged. The findings’ significant conflict might be somewhat due to contextual factors, such as industrial turmoil, aside from different model specifications and partially congruent research objectives. Campello et al. (2011) state that renegotiating credit lines during financial restructuring is a crucial determinant of turnaround success, and particularly when the overall economy is in decline. However, banks’ willingness to renegotiate strongly depends on such macroeconomic factors as upcoming recessions.
Various scholars in the finance research field supplement their research on the absolute level of debt by offering work on the composition of debt as an additional substream of research on financial restructuring during distress (Gennaioli and Rossi 2013). Asquith et al. (1994) and James (1996) note that debt composition is equally important for turnaround. Resorting to agency theory, Brown et al. (1993) state that the power shift from equity holders to creditors implies that the restructuring firm offers equity to private lenders and senior debt to public debt holders, leading to positive market reactions. Thus, debt covenants can act as an effective disciplinary mechanism during distress (DeAngelo et al. 2002). However, management and shareholders often counteract by trying to diminish creditors’ increase in power; managers and owners choose investment projects with lower net present values during distress to force creditors to accept poorer terms in private debt renegotiations, generating greater returns to shareholders in states of solvency (Bernardo and Talley 1996). Creditors as residual claimants will inevitably agree to concessions to avoid a costly liquidation, irrespective of a company’s state of distress (Mella-Barral 1999; Noe and Wang 2000; Routledge and Gadenne 2000). Thus, the decision to default can even be understood as the distressed firm’s endogenous response to anticipated foreclosure outcomes (Brown et al. 2006). Transaction costs for private debt restructuring remain comparably high due to these agency problems and limit the degree of debt structure alterations during distress (Gilson 1997). This argument yields an incentive for default, as transaction costs are significantly smaller.
3.4.2 Liquidity improvement
The regaining of sufficient liquidity is equally important as debt reduction and reorganization to turnaround efforts (John 1993). For instance, stretching accounts payable to improve liquidity is positively associated with turnaround (Chowdhury and Lang 1996). Furthermore, dividend cuts are observed as an additional liquidity improvement measure during distress. However, both conceptual and empirical findings remain inconclusive. While a reduction in dividends may result in immediate liquidity enhancements, the signaling effects to capital markets are negative (Eichner 2010). Buschmann (2006) cannot discover a significant impact on turnaround likelihood, and Sudarsanam and Lai (2001) even report slightly negative results. However, empiricism is still scarce and must account for the single occurrence of dividend cuts. Contrary to turnaround intuition, Castrogiovanni and Bruton (2000) conclude that parent companies’ simple infusion of capital to increase liquidity does not yield the desired outcomes, even worsening the distressed firm’s operating performance.
The aforementioned findings suggest that contextual factors are particularly important when analyzing liquidity improvements’ effects on turnaround success. Scholars’ models do not always clearly distinguish a firm’s health, hence impeding a summarization of the results between different studies. Additionally, a regional legislative framework is particularly important relative to creditor protection rights.
4 Turnaround process
Research on the turnaround process primarily resorts to life cycle approaches from the organizational change theory (Chowdhury 2002). Theorists argue that its effects depend on proper timing within the organizational life cycle (Agarwal and Gort 2002; Amburgey et al. 1993). The procedural aspects of turnaround still lack solid empirical proof, although they have been subject to conceptualization in many studies, and works that explicitly analyze different turnaround process stages remain underrepresented (Filatotchev and Toms 2006; Hoffman 1989; Pandit 2000; Pettigrew 2012). Nevertheless, how to implement turnaround fundamentally determines survival likelihoods (Bergh et al. 2008). Thus, turnaround content must be accordingly adjusted to the distressed entity’s organizational process stage (Barker and Mone 1994; Bibeault 1982).
Nevertheless, definitions for turnaround stages’ quantity, duration, or sequencing are hardly similar. However, various process models can be decomposed into principal retrenchment and subsequent recovery phases (Eichner 2010). Despite the multitude of preceding and adjacent stages offered in literature, studies analyzing turnaround success focus on measurable implementation phases that can be summarized under the aforementioned two stages. Consequently, turnaround activities under distress can be divided as either “defensive” or “belt tightening,” and “strategic” or “stabilizing” (Arogyaswamy et al. 1995; DeWitt 1993; Domadenik et al. 2008; Hambrick and Schecter 1983; Pearce and Robbins 1993). Further, the sense-making and communication strategy of distinct turnaround strategies depend on their respective process stages during the crisis (Balogun and Johnson 2004; Maitlis and Sonenshein 2010; Vaara et al. 2006). From a practitioner’s perspective, employing a turnaround process framework enables the effective prioritization of change strategies.
Bibeault (1982) refers to retrenchment-oriented actions as those to “stop the bleeding,” and target short-term stability during distress. Activities with the highest cash flow impacts should be chosen first during the retrenchment phase (Finkin 1985). However, scholars still argue about their applicability and effectiveness, depending on the context. While Robbins and Pearce (1992) conceptualize retrenchment as an integral component of a successful recovery, Barker and Mone (1994) and Castrogiovanni and Bruton (2000) argue that turnaround success is determined by both an implementation approach and the contextual factors of retrenchment strategies. Subsequently, Morrow et al. (2004) find industry conditions to significantly determine retrenchment success, stating that cost retrenchment is only positively related to improved performance in declining industries. Boyne and Meier (2009) further question the applicability of retrenchment actions in public sectors with their study on distressed school districts’ yielding adverse effects on survival rates.
Nevertheless, entering into a retrenchment phase as a reaction to corporate decline seems inevitable (Robbins and Pearce 1993). Moreover, Barker and Duhaime (1997) and Chowdhury and Lang (1996) find an increased likelihood of survival if private firms enter retrenchment phases. However, the synergy between retrenchment and recovery exceeds the effectiveness of solitary retrenchment moves (Schmitt and Raisch 2013).
Regarding the retrenchment phase’s intensity, most researchers support the implementation of severe cost-cutting actions during the initial turnaround phase. Bruton et al. (2003) report a positive relationship between the magnitude of implemented retrenchment strategies and firms’ survival. Furthermore, Denis and Rodgers (2007) find that firms are more likely to emerge as going concerns if they realize significant, severe asset and liability cuts during retrenchment. Lamont et al. (1994) offer more restrained results by highlighting a possible trade-off, in that firms with gradual turnaround moves recover faster, but with inferior post-distress performance compared to those that employ severe and rapid structural change. Sudarsanam and Lai (2001) contradict this by stating that managers in non-recovery firms restructure more intensively, yet more ineffectively than turnaround firms.
Regarding the retrenchment phase’s timing, scholars resort to the organizational inertia concept as part of the threat-rigidity theory (Wicks 2001), as retrenching actions should be initiated as soon as possible to ensure short-term stabilization (Jansen 2004; Moulton and Thomas 1993; Sheppard 1994). Large firms are especially disposed to organizational rigidity in the face of distress, as pre-distress inertia is already high (Audia and Greve 2006; Rosenblatt et al. 1993). However, in the specific corporate distress context, small firms that appear to be more flexible in a stable environment may become highly rigid as a result of low performance (Greve 2011). Van Witteloostuijn (1998) argues that organizational inertia even increases survival chances, as this enables firms to outlast their more rapidly moving competitors. Furthermore, organizations attempting to employ retrenchment-oriented moves as early as possible tend to increase risk in the face of distress (Chattopadhyay et al. 2001; Miller and Chen 2004). Zajac and Kraatz (1993) summarize this by positing that the pressure and “need to change” dominates the constraints of the “ability to change.”
This high dependency on organizational and contextual factors may explain the inconclusive results regarding the retrenchment phase’s timing and severity. Independent of contextual arguments, Barker and Mone (1994) note that the primary problem with analyzing retrenchment moves is the difficulty in distinguishing between the activity as merely the consequence of a crisis, or if it was proactively deployed as a deliberate turnaround strategy.
A subsequent shift toward sustainable growth is necessary after securing short-term stability through retrenchment (Pandit 2000). As recovery activities are based on investments, organizational refocus, and growth, a certain liquidity is necessary; hence, retrenchment might be an obligatory antecedent to an effective recovery phase (Eichner 2010). Although a recovery phase’s importance subsequent to retrenchment is conceptually established, the empirical white spot remains imminent. Hofer (1980) has defined three turnaround strategies that can be summarized as a recovery phase, stating that a successful turnaround either includes a product or market refocusing, or a “one-level” or “two-level” increase in market share; the latter comprises a 100 and 200% increase, respectively. Similarly, Finkin (1985) defines the “awakening” and “streamlining” as two out of the three primary turnaround phases.
One of the scarce empirical supports is offered by Sudarsanam and Lai (2001) who discover that recovery firms adopt growth-oriented and market-focused strategies, whereas non-recovery firms remain in the “fire-fighting” retrenchment stage. Eichner (2010) states that innovations during the recovery phase are highly effective in securing sustainable turnaround.
5 Turnaround context
Turnaround context, as summarized under the umbrella of contingency theory, comprises factors that are exogenous to the immediate scope of managerial actions (Pettigrew 1987). They are generally determined during the pre-distress phase to lay a comparable foundation for analyses. Ketchen et al. (1996) argue that context is an important control item to explain performance variations in connection with content and process. The current review expands Pettigrew’s (1987) framework, which defines context as either of an internal or external nature, and adds the cause of distress as a new third research dimension.
5.1 Underlying distress causes
Pandit (2000) classifies the distress cause as the most frequently researched context factor, in his review of 47 turnaround studies prior to 1996. Winn (1993) enables a systematic approach toward distress cause analysis by defining various types of corporate deterioration and argues that each must be met with distinct turnaround strategies. Asquith et al. (1994) and Giroud et al. (2012) divide crisis causation into cash flow components by distinguishing between such internal causes as high leverage or weak operating performance, and such external causes as industry decline.
5.1.1 Internal distress causes
Firm-specific distress causes, such as high leverage, low operating profitability, or overexpansion, fall under the managers’ potential influence and are thus often observed as endogenous root causes. Various turnaround researchers argue that these controllable factors contribute to avoiding default more than exogenous factors (Francis and Desai 2005).
Regarding operating profitability, Hofer (1980) conceptualizes that firms operating close to breaking even use retrenchment strategies to achieve turnaround, whereas firms operating far below this point should employ portfolio restructuring and revenue-increasing actions. Furthermore, if operational profitability problems are technology based, a turnaround strategy must be chosen accordingly, as this distinctly differs from mere cost cutting (Lin et al. 2006).
The finance research field offers the majority of publications on overleveraging as a cause of crisis, finding positive correlations between the severity of financial distress and default probability (Campbell et al. 2008; Ofek 1993; Pandit 2000; Smith and Graves 2005). Campello et al. (2010) argue that firms with tight credit constraints inevitably plan deeper retrenchments regarding technology and capital investments, and are forced to lay off more staff, leading to an inability to achieve long-term profitability after the immediate distress situation.
Although the factors determining internal distress causes are defined ex-ante, researchers face endogeneity problems (Giroud et al. 2012). While high leverage and underperformance are antecedents to corporate distress, they are often also caused by decline and emerge as a result of turnaround efforts; hence, they cannot be clearly stated as independent when developing a turnaround model.
5.1.2 Exogenous distress causes
Comprising factors that are not directly influenced by the firm’s management are leaps in competition or sudden technology changes, industry conditions, or legislation changes, external distress causes are not directly influenced by the firm’s management (Mellahi and Wilkinson 2004). Denis and Denis (1995a) conclude that turnaround probability depends on unexpected macroeconomic, industry-wide factors. Furthermore, Das et al. (2007) find that corporate defaults cluster over time. The authors provide three explanations for this: (1) firms may be exposed to common risk factors yielding correlated changes in default probabilities; (2) the default of one firm may lead to a chain reactions, forcing rivals into distress; and (3) legislators may learn from corporate defaults, leading to legal changes and increasing rivals’ default probabilities. Tushman and Rosenkopf (1996) highlight this importance by discovering that management replacement is positively associated with post-turnaround performance, but significantly and negatively associated with subsequent performance when industry turmoil is the cause of distress.
A commonly researched exogenous cause of distress involves industry crisis. Finance and managerial research scholars agree that distress is more likely to occur during industry turmoil (Almeida and Philippon 2007; Ramanujam 1984). Campello et al. (2011) argue that corporate credit lines decrease during an industry crisis, leading to corporate distress, but Benmelech and Bergman (2011) find that a firm’s default reduces other industry rivals’ collateral value, leading to a bankruptcy chain reaction. The latter argue that oversupply of corporate assets due to multiple portfolio restructurings leads to an industry-wide value reduction, and thus a magnification of the crisis. Andrade and Kaplan (1998) pursue this argument by concluding that economic shocks drive higher distress costs, significantly influencing the chosen strategy’s effectiveness. However, Moulton et al. (1996) and Knott and Posen (2005) argue that distressed firms generate externalities that significantly reduce industry-wide costs, eventually leading to beneficial economic effects.
Various turnaround moves yield inconclusive results, or even reverse effectiveness, when explicitly accounting for exogenous distress causes (Mitchell and Mulherin 1996). A prominent example involves Lin et al.’s (2008) study, which discovers an increasing probability of default during recessions, in which companies massively reduce their workforce or downsize large-scale assets, commonly effective actions during a turnaround. Comparably, Loui and Smith (2006) conceptualize management replacements as particularly counterproductive during recessions, and similar results are found regarding portfolio restructuring. Wan and Yiu (2009) state that corporate acquisitions during environmental crises more positively relate to post-crisis performance than in periods either before or following an industry crisis.
A lack of empirical research to compare various turnaround strategies, contingent on root causes, becomes evident when summarizing the work on underlying distress causes as contextual factors.
5.2 Microeconomic context
Factors describing firm-specific characteristics are summarized under a microeconomic context. Thomas and Ramaswamy (1993) conclude that organizational context is a pivotal determinant of organizational change. Moulton et al. (1996) further argue that firm effects dominate industry effects in explaining failure. Coucke et al. (2007) find that age, labor intensity, profitability, and size are the most influential moderators for turnaround actions’ effectiveness. Indro et al. (1999) note ownership structure as an additional measurable context factor. Nevertheless, Lin et al. (2006) state that no optimal mix of firm characteristics exists to securely deter default.
The most commonly included context variable is firm size, which some scholars claim dominates all other turnaround likelihood factors (Greve 2011; Moulton and Thomas 1993; Robbins and Pearce 1993). The direction of this causality seems unambiguous, with a positive correlation between firm size and survival chances (Agarwal et al. 2002; Ahmadjian and Robinson 2001; Kato 2010; Ramanujam 1984; Stoeberl et al. 1998). For instance, Campbell et al. (2008) find that Chapter 11 firms are on average ten times smaller than surviving firms. However, Denis and Rodgers (2007) and Pant (1991) argue that larger firms cannot reorganize as quickly as their smaller counterparts under distress, thus having inferior chances of survival. D’Aveni (1989) further generally questions the influence of size as a contextual factor. Some scholars similarly emphasize an organization’s age as having significantly higher variance explanation power than mere size (Cefis and Marsili 2005; Klepper 2002; Thornhill and Amit 2003). However, this argument must be interpreted with caution, as size and age as independent context variables are hardly immune to confounding.
Ownership becomes an important moderator of turnaround moves’ effectiveness with respect to information asymmetries and dispersed interests between stakeholders and management during corporate distress (Mata and Portugal 2000). Donoher (2004) and Lai and Sudarsanam (1997) find that ownership structure and corporate governance highly influence the choice of recovery strategy. However, empirical evidence remains mixed; Filatotchev and Toms (2003) and Geroski and Gregg (1994) find that large institutional ownership is positively associated with survival, but Mata and Portugal (2000) cannot find any significant effects.
The consideration of various ownership structures becomes highly relevant when state-owned entities are analyzed. Scholars find significantly different turnaround approaches and effects when comparing stock corporations, state-owned firms, and privately held companies (Vicente-Lorente and Suárez-González 2007).
Further, works on domestic versus foreign ownerships emphasize the negative effects of the latter. However, Mata and Portugal (2002) cannot report significant differences in survival chances between domestic and foreign firms. Kronborg and Thomsen (2009) further note a significant survival premium for non-domestic firms. Possible explanations are offered by Vicente-Lorente and Suárez-González (2007), who summarize that due to their cultural background, foreign firms are characterized by more heterogeneous downsizing behaviors compared to domestic market participants, yielding ambiguous results.
Many additional underlying factors influence turnaround probability aside from the two primary microeconomic context variables. For instance, Hovakimian et al. (2012) state that lower asset tangibility positively relates to default risk, and Tong and Wei (2011) offer similar results for the dependence on non-foreign direct investments. Agarwal et al. (2002) reference the product life cycle theory and state that the time of entrance into a product market significantly influences survival chances, as mature phase entrants are considerably more prone to decline than early and growth phase entrants. Similarly, Geroski et al. (2010) find a “founding effect,” summarizing that the founder’s educational background, current GDP growth, and other firm characteristics at the time of founding impact the firm’s survival for several years. Studies by Mutchler and Hopwood (1997) and Faccio et al. (2006) offer softer factors, with the former emphasizing the explanatory power of news reporting on the company’s default, and the latter positive associating a firm’s political connections with turnaround likelihood.
The employed microeconomic context variables’ high diversity may explain the contradictive empirical results, and especially when considering characteristics that are difficult to operationalize, such as a firm’s culture; unobserved heterogeneity among the bankruptcy models may yield mixed results.
5.3 Macroeconomic context
Silverman et al. (1997) argue that firm mortality is influenced by not only firm-specific microeconomic contexts, but also industry-level attributes. Default risk includes a systematic component from a conceptual perspective, aside from company-specific idiosyncratic risk, which is contingent on macroeconomic factors and causes spillover effects as well as industry-specific yet time-varying risk factors (Giesecke and Kim 2011; Vassalou and Xing 2004).
Institutional legitimacy plays a prominent role in conceptualizing the corporate reaction to decline and survival chances (Shane and Foo 1999). Operational restructuring is often especially constrained by legitimacy problems (Ahmadjian and Robinson 2001; Lynn and Rao 1995). Hence, Moulton and Thomas (1993) conclude that turnaround activities are highly constrained by forces external to the organization. Dawley et al. (2002) state that these macroeconomic constraints can even yield default. Thus, different archetypes of environmental settings, such as industry volatility, high environmental complexity, or a combination of both must be considered (Siggelkow and Rivkin 2005). Consequently, manifold outer context variables are discussed in turnaround research; a majority of works cover the influence of legislation, industry, and regional characteristics.
The statutory environment directly impacts a firm’s reaction to decline aside from mere procedural variations in different legal settings (Mouly and Sankaran 2004). For instance, Davydenko and Franks (2008) argue that a lack of creditor protection leads banks to adjust their lending practices and require more collateral, thus increasing firms’ bankruptcy costs. Acharya and Subramanian (2009) similarly find a positive association between debtor-friendly bankruptcy codes and the use of innovation. When accounting for strong union laws combined with weak investor protection, Atanassov and Kim (2009) identify alliances between workers and managers who sell assets to prevent layoffs, even willingly risking further declines in performance. Further, Lel and Miller (2008) state that firms from weak investor protection regimes, which are cross-listed on US markets, have a greater likelihood to employ CEO replacement as a means of turnaround.
Industry effects resorting to systematic default risk as a macroeconomic context are highly significant in default prediction models (Chava and Jarrow 2004; Rosenblatt and Mannheim 1996). Routledge and Gadenne (2000) empirically support that retail companies fail considerably more often than firms from the manufacturing sector. Similarly, Hancock et al. (2013) discover that layoffs’ effectiveness significantly increases in manufacturing firms compared to other industries.
Behavioral theorists argue that both industry characteristics and regional and cultural influences impact the choice of turnaround strategy (Bruton et al. 2003). However, as most studies base their results on samples from the USA, empirical evidence remains scarce. Kang and Shivdasani (1997) and Hurry (1993) compare turnaround moves in distressed firms in the USA with Japanese organizations and find that the latter are less likely to downsize and the extent of layoffs is significantly smaller than in US companies. Bruton et al. (2003) broaden the analysis to East Asian companies in general and argue that cultural differences, operationalized by the power of a firm’s owner managers and their relationship to their colleagues, constrain the applicability of workforce reduction.
6 Turnaround outcome
Although most works on corporate turnaround operationalize both distress and turnaround success, only a few studies deliberately discuss the theoretical grounding and reasoning for the chosen measure (Winn 1993). However, our framework accounts for the importance of correct success measurements, compares common measures across research fields, and is supplemented by the meta-dimension of turnaround outcome. As Eberhart et al. (1999) demonstrate, the choice of performance metrics significantly determines the study results. The authors compare their findings, measured in abnormal returns (AR), with previous studies that resort to operating performance as a main measure. Furthermore, Holder-Webb et al. (2005) indicate that operational restructuring’s positive AR result from market expectations is a response to restructuring announcements. Hence, when controlling for these positive reactions, the authors conclude that operational restructuring does not improve long-term performance.
Pandit (2000) identifies overreliance on accounting measures as a common default in turnaround research. The differences in success measures become apparent, and especially when comparing works from the fields of general management and finance research. Moreover, the difference between accounting-based and market-based measurements plays an important role when reviewing studies on turnaround outcomes. Eberhart et al. (1999) find that market-based measures yield positive abnormal returns after Chapter 11 bankruptcy for US firms, a success measure primarily employed in the finance research field. However, Hotchkiss (1995) offers contradictive results that employ accounting measures, predominantly used in general management research. Although scholars rely on market measures to argue that relative and absolute accounting measures can be subject to managerial manipulation, the counterparty claims market measures are biased by expectations (Eberhart et al. 1999; Franzen et al. 2007; Furrer et al. 2007).
Moreover, as Haleblian et al. (2009) advocate in their concluding remarks on measurement issues in M&A research, short-term abnormal market returns lack the crucial ability to measure value creation or destruction during implementation phases; the same applies to corporate turnaround research. As emphasized during the review of such operational restructuring moves as organizational process restructuring, not all firm turnaround efforts are visible to outsiders. A detailed analysis of the accounting metrics used reveals potential flaws in accounting-based measurements. While cash flow shortfalls to cover debt payments are often used to determine distress situations, the use of calculations employing earnings before interest and tax minus CAPEX and interest payments imply the hazard of misinterpreting firms’ CAPEX characteristics (Eichner 2010). Entities pursuing substantial investments, and thus experiencing a significant yet punctual CAPEX increase, might be classified as distressed under the aforementioned criteria, despite offering healthy firm conditions (Pun and White 2005). Hence, operationalizing a defined success measure directly influences research results.
However, recent research struggles to offer clear advancements on the subject. For instance, Trahms et al. (2013) suggest a more detailed differentiation of turnaround outcomes, introducing several distinct outcome categories: sharp-bend recovery, premium M&A, simple recovery to moderate recovery, discounted M&A, reorganization, and failure, but these fall short of operationalizing the different categories. The differentiation between sharp-bend, simple, and moderate recoveries might be especially difficult to determine.
A more qualitative approach toward measuring turnaround strategies’ effectiveness might be suitable to overcome these shortcomings. Works from management research especially offer alternative concepts of quantifying turnaround outcome. For instance, Acharya and Subramanian (2009) use a firm’s number of patents and R&D investments to indicate turnaround success. Love and Kraatz (2009) use changes in reputation as an additional measure of turnover strategies’ effectiveness. From the finance research field, Benmelech and Bergman (2011) use credit spread differences during distress and turnaround as success indicators. While these alternative turnaround outcome measurements provide additional advantageous insights into turnaround strategies’ true effects, they also imply a disadvantage of low comparability.
Consequently, turnaround outcomes must always be compared by considering the underlying research objective as well as the corresponding research field (Winn 1993). An additional challenge results from the myriad of definitions employed (Lai and Sudarsanam 1997; Scherbaum and Meade 2013).
7 Future research agenda
Research gaps and future research agenda
Reason for research gap
How to address
Gap 1: Integration of lenses
The majority of publications from the finance and management lens remain mostly detached, although no single turnaround move has sufficient explanatory power when evaluating its turnaround efficiency
Emphasize the investigation of interdependencies between moves from different disciplines
How do financial restructuring moves interplay with operational restructuring?
What influence does portfolio restructuring have on management replacement?
How can interdependencies of turnaround strategies be controlled for?
Gap 2: Theoretical grounding
Although turnaround research is commonly based on organizational change theory, various publications lack solid theoretical grounding or resort to concepts exclusive to the respective research field
As Pettigrew (2012) suggests, a strong theoretical foundation and explicit goals of theory generation are needed
Further, emerging disciplines like behavioral finance should be integrated
Including the concept of behavioral irrationalities, what cognitive biases can help explain threat-rigidity responses in distressed firms?
How do behavioral anomalies such as self-attribution bias of the CEO affect management replacement effectiveness?
Gap 3: Sample characteristics
Various sample biases exist in the reviewed body of research: large company bias; overrepresentation of manufacturing industries; exclusion of financial service industries; choice-based bias; US bias. Thus, integration of findings is hindered
Employ more international samples and broadcast the use of matched-pair samples to account for industry characteristics and make region-by-region comparisons
How are different turnaround strategies contingent on regional differences?
How does the effect of different turnaround moves differ between crisis causation?
How do turnaround behavior and success of the banking sector differ compared to manufacturing firms?
Process and context
Gap 4: Content–context–process interdependencies
Comprehensively accounting for the interplay between turnaround content, process, and context remains a white spot in most publications
Include time-variant process variables in dynamic modeling and controlling for internal and external context
How can the existing contradiction on effectiveness of CEO replacement, portfolio divestment as a means of portfolio restructuring, and debt restructuring as part of financial restructuring be resolved by integrating time-variant process and context variables?
Gap 5: Accounting for timing
Most empirical studies on corporate turnaround are based on cross-sectional data only. Longitudinal large sample studies are scarce. This lack of longitudinal turnaround research hinders scholars to effectively link content to process and establish consistency regarding turnaround time frames
Use dynamic panel data models, enabling researchers to account for firm-specific and industry-specific fixed effects as well as time-variant influences. Outcome variation could thus be linked to distinct process patterns, increasing the explanatory power of turnaround models
Does post-bankruptcy performance represent final firm profitability or is it rather an intermediate effect?
How long does the impact of individual turnaround moves lag behind implementation?
Gap 6: Recovery phase research
Empirical works explicitly analyzing the effect of recovery phase turnaround strategies remain scarce
Although it is difficult to disentangle explicit turnaround effects from pure efficiency-enhancing moves in stable times, scholars could address this gap by controlling for inner context and broaden empirical turnaround models to include recovery- and growth-oriented moves
How does the effectiveness of turnaround moves differ when implemented in stable context compared to distress situations?
How much variance explanation power do recovery-oriented moves offer?
What interdependencies between retrenchment and recovery strategies exist?
Gap 7: Consistent success metric
In addition to the conflict between accounting and market-based metrics, turnaround research holds further difficulties regarding a consistent distress and success measurement. Since some turnaround moves lack the ability to yield measurable value creation during implementation, a consistent evaluation becomes difficult
Employ twofold turnaround models, including accounting-based as well as market-based measures. Additionally, include a more precise definition of turnaround success to avoid misinterpretations of empirical findings
How can firms incorporate the interplay between market expectation and financial performance into the turnaround strategy development process?
How can corporate distress effectively be measured, accounting for the internal and external context?
Gap 8: Enhancement of bankruptcy prediction models
Most empirical studies reviewed resort to logistic regression analyses, which are unable to account for the dynamics of organizational turnaround. Further, most models are limited to quantitative data and dichotomous operationalization of variables. Qualitative dimensions such as firm culture changes are mostly neglected
Incorporate questionnaire results as well as qualitative panel data sets into dynamic hazard models. Furthermore, studies investigating single events over a longer period of time in great depth could help enhance the theoretical grounding for future turnaround models
How does research on firm culture changes during turnaround interplay with financial distress cost analyses?
Gap 9: Potential confounding and endogeneity
The danger of endogeneity in research models remains neglected. The reversed causality problem could lead to a misinterpretation of findings
Resort to multiple-stage regression models, using instrument variables to secure the right model specifications
The enhanced methodology would enable researchers to reinvestigate some still inconclusive empirical findings in turnaround research, possibly finding alternative factor loadings for individual moves, timing, or context items
7.1.1 Gap 1: Integration of lenses
As this review demonstrates, different theoretical lenses must be referenced to account for the breadth of restructuring research. The turnaround actions embedded in the framework draw from various and partially detached disciplines (Eichner 2010). However, as Pettigrew (2012) summarizes, no single move has sufficient explanatory power when investigating organizational performance. Nevertheless, the vast majority of works from the finance and management lens remain detached. Haleblian et al. (2009) describe this phenomenon as emphasizing two sides of the same coin without real integration, consequently resulting in a lack of integrated findings.
This begins with an inconsistent use of the terminology. For instance, while the majority of management research works refer to downsizing as a turnaround move, such as through employee layoffs (Filatotchev et al. 2000), the same term used in finance literature researches the effect of asset reductions on turnaround probability (Denis and Denis 1995a). If the studies’ individual backgrounds are not considered, a meta-analysis of downsizing efficiency inevitably yields spurious conclusions. Further, as stated in the discussion on turnaround success definitions, using different measures to determine the effect on turnaround likelihood for similar turnaround strategies might again lead to incorrect results. Future research could best address this by emphasizing the investigation of interdependencies between moves from different disciplines, following Francis and Desai’s (2005) example. The authors offer a holistic view on turnaround strategies by accounting for different situational settings in combination with restructuring moves. Hence, the resulting research questions could include: “How do financial restructuring moves interplay with operational restructuring content?”, “How does portfolio restructuring influence management replacement?”, or “How would one control for the interdependencies of restructuring strategies?”
7.1.2 Gap 2: Theoretical grounding
A second and partially related gap results from insufficient theoretical grounding (Loui and Smith 2006). Restructuring work is commonly based on either agency theory (Barker et al. 2001; Espen and Thorburn 2003; Gibbs 1993; Gilson 1989) or organizational process theory (Chowdhury 2002; Ketchen and Palmer 1999; Pettigrew 1987, 2012), to name two prominent examples. However, various publications lack solid theoretical grounding, or resort to concepts exclusive to the respective research lens (Pandit 2000). Thus, as Pettigrew (2012) suggests, strong theoretical foundations and explicit theory generation goals are required, which will enable scholars to employ deductive research and a superior understanding of empirical findings. A further possibility to address this eminent gap involves integrating newly emerging disciplines, such as behavioral finance; a prominent example is Carmeli and Sheaffer’s (2008) work on how organizational learning from failure affects leadership. The incorporation of alternative disciplines leads to a new spectrum of research questions, such as: “Including the concept of behavioral irrationalities, what cognitive biases can help explain threat-rigidity responses?” or “Is managerial restructuring influenced by such behavioral anomalies as the CEO’s self-attribution bias?”
7.1.3 Gap 3: Sample characteristics
The body of research on restructuring content reviewed in the current work is largely subject to various sample biases. Aside from a large company bias, as identified by Robbins and Pearce (1993) and Chowdhury and Lang (1996), manufacturing industries are heavily overrepresented and most financial service industries are excluded (Chava and Jarrow 2004). Although Shumway’s (2001) bankruptcy prediction model offers a rare exception, the representation bias hinders a solid integration of findings. Zmijewski (1984) describes two additional sample biases by highlighting potential choice-based and selection biases, primarily due to limited data availability. Furthermore, as most samples are heavily biased toward the USA, transferring these findings to other regions is difficult (Bruton et al. 2003). This lack of an integrative data sample can be diminished by employing more international samples and broadcasting the use of matched-pair samples (Pettigrew 2012). This enables scholars to more deliberately control for industry characteristics and make comparisons among regions. The following potential research questions emerge by overcoming these common limits in sample characteristics: “How are different restructuring strategies contingent on regional differences?”, “How do the effects of different restructuring moves differ between external and internal crisis causes?”, “How do restructuring behaviors and successes in the banking sector differ compare to those in the manufacturing industry?”
7.2 Process and context
7.2.1 Gap 4: Content–context–process interdependencies
Although a majority of more recent publications incorporate some form of context contingency into their research, the various inconclusive findings disclosed in this review hint to a prevailing lack of comprehensive accounting for the interplay between restructuring content, process, and context (Holder-Webb et al. 2005). As Pettigrew (2012: 1309) summarizes, in his retrospective on organizational process research, “the biggest challenges and pay-offs come from us attempting to carry out process and outcome studies where there is an explicit attempt being made to explain the determinants of outcome variation in context and process terms.” Researchers can address this gap by deliberately including time-variant process variables in dynamic modeling and controlling for internal and external context (Datta et al. 2010). Scholars can use a dynamic content–process–context framework to better explain variations in restructuring efficiency and enhance turnaround models. Possible research areas include the resolution of existing contradictions on the effectiveness of managerial restructuring, portfolio divestment as a means of portfolio restructuring, and debt restructuring as a part of financial restructuring.
7.2.2 Gap 5: Accounting for timing
An important gap becomes obvious when accounting for the fact that most empirical corporate restructuring studies are only based on cross-sectional data. Pandit (2000) concludes in his review that large longitudinal sample studies are scarce. This lack of longitudinal restructuring research hinders scholars to effectively link restructuring content to the process (Pettigrew 2012). Additionally, various scholars note a lack of consistency regarding clearly defined restructuring time frames (Smith and Graves 2005; Stopford and Baden-Fuller 1990). As Chowdhury (2002) points out that allowing for a certain time span is critical, as most restructuring actions yield lagged results. However, if the chosen time frame is too short, a specific move’s true effects might be excluded, and if too broad, model noise rapidly increases. Researchers could address this gap by resorting to dynamic panel data models, enabling them to account for both firm-specific and industry-specific fixed effects, as well as time-variant influences (Brauer 2006). The outcome variation could thus be linked to distinct process patterns, increasing the turnaround models’ explanatory power. The resulting research questions include: “Does post-bankruptcy performance represent a firm’s final profitability, or is this an intermediate effect?”, “How long do individual turnaround moves’ impacts lag behind implementation?”, and “When should an individual restructuring activity be best implemented to release its full potential during the turnaround phase?”
7.2.3 Gap 6: Recovery phase research
The restructuring process literature review revealed few works regarding recovery phase turnaround. Although the conceptual grounding and theoretical justification of this phase is solid, empirical publications that explicitly analyze recovery-oriented restructuring moves remain rare (Eichner 2010). Moreover, Barker and Mone (1994) describe the difficulty in disentangling explicit turnaround effects from pure efficiency-enhancing moves in stable times, as this becomes especially problematic when analyzing growth-oriented restructuring moves. However, the results fundamentally differ between the contexts of forced restructuring in the face of bankruptcy or voluntary reorganization (Love and Nohria 2005; Tushman and Rosenkopf 1996). Scholars could address this research gap by comprehensively controlling for inner contexts and broadening empirical turnaround models to include recovery- and growth-oriented moves, such as innovation efforts. Various research questions arise to account for this gap: “How do restructuring moves’ effectiveness differ when implemented in stable contexts, compared to distress situations?”, “How much variance explanation power do recovery-oriented restructuring moves offer?”, or “What interdependencies exist between retrenchment and recovery strategies?”
7.3 Methodological issues
7.3.1 Gap 7: Consistent success metric
One explanation for the various empirical contradictions disclosed in this review involves the underlying performance metrics and distress criteria used. As Winn (1993) states, publications often lack a proper evaluation and theoretical grounding of the metrics used to define distress and the subsequent turnaround success or failure. Pandit (2000) identifies an overreliance on accounting measures to indicate turnaround success as a common default in restructuring research. While Eberhart et al. (1999) find that market-based measures yield positive abnormal returns after Chapter 11 bankruptcy, Hotchkiss (1995) offers contradictive results that employ accounting measures. Haleblian et al. (2009) conclude that in an M&A context, short-term abnormal market returns may provide an efficient performance metric, but they clearly lack the crucial ability to measure value creation or destruction during implementation phases. The same problem exists in corporate restructuring research. As already stressed during the review of operational restructuring moves, not all firm efforts to achieve turnaround are visible to outsiders. However, Chava and Jarrow (2004) postulate that accounting variables add little predictive power when market measures are already included in bankruptcy analyses. As mentioned previously, a detailed analysis of the accounting metrics used reveals the potential flaws in accounting-based measurements, and, as such, entities experiencing substantial investments and thus significant yet punctual CAPEX increases could be classified as distressed, despite offering healthy firm conditions.
Scholars should address this eminent lack of conclusive measurements by employing twofold restructuring models, including both accounting- and market-based measures. For example, Shumway’s (2001) bankruptcy prediction model accounts for past stock returns as well as corporate profitability. Moreover, following Haleblian et al.’s (2009) argument, more precisely defining restructuring success avoids misinterpretations and false generalizations in the empirical findings. The development of a comprehensive matrix model, with research objectives as the first dimension and available distress and outcome metrics as the second, would provide additional clarification. Hence, this could offer a unified approach toward measuring the effect of different restructuring activities. Researchers could interpret restructuring effectiveness based on this twofold approach and the following research questions: “How can firms incorporate the interplay between market expectations and financial performance into the turnaround strategy development process?” or “How can corporate distress be effectively measured to account for both internal and external contexts?”
7.3.2 Gap 8: Enhancement of bankruptcy prediction models
Most of the reviewed empirical studies resort to a logistic regression analysis, which Brauer (2006) argues cannot account for the dynamics of organizational restructuring. Although notable methodological developments have been realized when using Altman’s (1968) bankruptcy prediction model as a starting point, a methodological gap remains in accurately predicting turnaround, linking content to process and context. Ohlson (1980) was one of the first to incorporate various mediators in his model, but Shumway (2001) finds this to be incorrectly specified, enhancing predictability by offering a dynamic hazard model. Chava and Jarrow (2004) further modify the model to be applicable to both longitudinal monthly data and the often-excluded financial service sector, again increasing its explanatory power. However, most models are limited to quantitative data and dichotomous variable operationalization, and such qualitative dimensions as firms’ cultural changes are mostly neglected. Future works could address this gap by incorporating both questionnaire results and qualitative panel data sets into dynamic hazard models. Studies argue in the same vein as Haleblian et al. (2009) by investigating single events over a longer period of time in great depth, which could enhance the theoretical grounding for future bankruptcy prediction models. The resulting research questions are manifold, linking quantitative to qualitative internal and external context and integrating different social science research studies. For instance: “How does the combination of human capital research on firm culture during turnaround interact with financially distressed cost analyses?”
7.3.3 Gap 9: Potential confounding and endogeneity
Finally, a common deficit of empirical performance analysis is the danger of endogeneity found in research models. The reversed causality problem, as discussed by Barker et al. (2001) and Giroud et al. (2012) could lead to a misinterpretation of findings. Giroud et al. (2012) demonstrate in their study of corporate default that linking a significant reduction in leverage to an increase in firm performance can reverse causality. This is primarily because the anticipation of performance improvements might lead banks to forgive debt, thus decreasing a firm’s leverage. Molina (2005) similarly argues that ignoring the endogeneity of leverage can lead to an underestimation of its effect on default probabilities. Researchers could address this methodological gap of underestimating the endogeneity in context items by resorting more often to multiple-stage regression models, using instrumental variables to secure the correct model specifications. This enhanced methodology would enable researchers to reinvestigate inconclusive empirical findings on restructuring research, possibly finding alternative factor loadings for individual restructuring moves, timing, or context items.
This article aims to provide a comprehensive review and consolidation of corporate turnaround research across various research streams. We contribute to turnaround literature by offering a consolidation of 262 publications across multiple research streams and theoretical perspectives, guided by a comprehensive framework. Resorting to the more detailed corporate restructuring research classifications, we can overcome the potential shortcomings of a merely dichotomous classification according to “operational” and “strategic” turnaround actions and provide a more detailed analysis of the numerous facets of turnaround during corporate distress. The review holistically approaches the topic and considers a broad range of substreams on turnaround content, processes, and contexts, as well as the interdependencies between the various disciplines. We propose a research agenda based on a comprehensive review, by deriving potential research opportunities from systematically identified gaps in corporate turnaround research. Specifically, we discuss challenges in accurately measuring turnaround outcomes by contrasting the success measures employed by different research streams. This article lays a foundation for the prospective future “high tide” in turnaround research, following the turmoil of the 2008 global financial crisis.
Selected journals are as follows: Management: Academy of Management Journal, Administrative Science Quarterly, Journal of International Business Studies, Journal of Management, Journal of Management Studies, Management Science, Organization Science, Organization Studies, Research on Organizational Behavior, Strategic Management Journal, and International Journal of Management Reviews; Finance: The Journal of Finance, Journal of Financial and Quantitative Analysis, Journal of Financial Economics, and Review of Financial Studies; Economics: American Economic Review, Industrial & Corporate Change, Journal of Economics and Management Strategy, Journal of Economic Perspectives, and RAND Journal of Economics; Accounting: Accounting Review, Journal of Accounting and Economics, and Journal of Accounting Research; Sociology: American Journal of Sociology and American Sociological Review.
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