Relatedness

Again, reflecting the ideas proposed by Ansoff’s (1965) framework, the degree of similarity between an acquiring and target firm, or relatedness, is a common focus of strategic management research (Hitt et al., 2009). Generally, research expects a positive impact for relatedness on acquisition performance for several reasons. One has to do with resource similarity allowing more efficient use of available assets. Similarity also is beneficial due to less information asymmetry and lower managerial demands for firms operating in the same areas (Carey, 2000; Chakrabarti & Mitchell, 2016; Flanagan & O’Shaughnessy, 2003). Considerable literature supports this perspective with multiple studies supporting a positive impact of relatedness on acquisition success (Goldberg & Goodwin, 2001; Homberg, Rost, & Osterloh, 2009; Kim & Finkelstein, 2009; Park, 2003, Maksimovic & Phillips, 2001; Maquieira, Megginson, & Nail, 1998). Most research uses industry codes to measure relatedness. However, different effects for product market and technology relatedness may not be consistently captured by industry code measures of relatedness (Homberg et al., 2009; Lee & Kim, 2016.

Although intuitively appealing, assumptions of value potential based on overall firm similarity have been questioned. Zaheer, Castaner, and Souder (2007) outline that different dimensions of relatedness are not simply additive, or some aspects of relatedness can hinder improvement on other dimensions. Different effects for relatedness may reflect observations that acquisitions involve costs in addition to planned savings (Selden & Colvin, 2003), or both gains and costs from related acquisitions can be higher (Meyer, 2008). For example, in addition to greater demands for integration, related acquisitions also have a larger impact on suppliers and customers (Anderson et al., 2001) that could contribute to retaliation that lowers the benefits from an acquisition (King & Schriber, 2016; Rogan & Greve, 2014). This may be consistent with diminishing returns from relatedness, and Palich, Cardinal, and Miller (2000) suggest an inverted-U relationship exists between relatedness and performance.

Contradicting expectations on the effect of relatedness begin to explain why a prior meta-analysis (King et al., 2004) and an updated meta-analysis did not find significant correlations between relatedness and different measures of acquisition performance. These results hold across multiple measures of acquisition performance (e.g., stock market reactions, accounting, and managerial assessment). One interpretation is that relatedness may influence acquisition performance, but existing research and measures are not able to identify its source. Further research on relatedness using different measures needs to explore whether relatedness is a multi-dimensional construct, or it displays a curvilinear relationship with performance (e.g., Palich et al., 2000). Unfortunately, not enough research examines relatedness with similar measures to test for curvilinear effects with meta-analysis. Additionally, the impact of different types of relatedness is likely moderated by other contextual variables (Patel & King, 2016). In other words, there is a need for research to continue to develop different dimensions of relatedness and to explore complex relationships of relatedness with performance.

Cultural distance

Although conceptualizations vary, in general, culture is regarded as often unarticulated, views and norms about how things should be, and significant differences can create unanticipated problems during acquisition integration. While there are expectations that cultural distance has an overall negative effect (e.g., Bebenroth & Hemmert, 2015; Goerzen & Beamish, 2003), cultural distance can offer positive effects through novel knowledge and means of bridging national borders (Reus & Lamont, 2009; Patel & King, 2016; Stahl & Voigt, 2008; Vaara, Sarala, Stahl, & Bjorkman, 2012). While cultural distance presents increased challenges for an acquirer (Bresman, Birkinshaw, & Nobel, 1999; Dewenter, 1995; Hutzschenreuter, Voll, & Verbeke, 2011; Slangen & Hennart, 2008), there is limited research on how to mitigate problems from cultural distance (Rottig, 2011).

A prior meta-analysis found the impact of cultural distance in M&A research was inconclusive (Stahl & Voigt, 2008), an examination including more recent studies finds a negative correlation between cultural distance and short-term stock market performance. However, the challenges of cross-border acquisitions extend beyond culture to include language and geographic distance (Risberg, 2001). While there is limited research on the impact of language distance in acquisitions (Kedia & Reddy, 2016), one-third of domestic preference for firm investments may be due to geographic proximity (Coval & Moskowitz, 1999). As a result, there is a need to control for geographic distance in research examining cultural distance in cross-border acquisitions (Dow & Larimo, 2009; Stahl & Voigt, 2008). Unfortunately, not enough existing research uses common variables to measure geographic distance, rendering it impossible for us to aggregate the effects of geographic distance.

Prior performance

The performance of both an acquirer and target is likely relevant in predicting the future. In other words, a firm’s performance following an acquisition is likely associated with its performance before an acquisition (Krishnan, Miller, & Judge, 1997), and this can also influence target selection (Park, 2003). Similarly, a target firm’s prior performance can reflect different motives for a takeover. On one hand, acquirers often target high performing firms for acquisition (e.g., Saxton & Dollinger, 2004), or select the most attractive target firm (Toxvaerd, 2008). On the other hand, acquisitions can replace managers at struggling firms (e.g., Bilgili, Calderon, Allen, & Kedia, 2017), and acquisitions of bankrupt assets increase acquisition performance (Jory & Madura, 2009).

A meta-analysis to aggregate results of current research shows the prior performance of an acquiring firm is not significantly correlated with stock market measures of performance. However, there is a strongly significant positive relationship with accounting performance and a significantly positive correlation with managerial assessment of performance. This finding is consistent with the stock market having difficulty predicting long-term acquisition performance and that managerial assessment of acquisition performance may be consistent with archival measures. Further, when considering target firm performance prior to an acquisition, there is a significantly positive correlation with accounting measures of acquisition performance. However, research does not consistently control for prior performance, and (if it does) research is much more likely to consider prior performance of an acquiring firm. Future research is encouraged to include both acquirer and target firm performance as a research control.

Acquirer R&D

Acquiring firm R&D intensity has been observed to be significantly lower than industry averages (King et al., 2008), suggesting acquirer R&D serves as an absorptive capacity for target firm R&D resources (De Beule & Sels, 2015; Heeley et al., 2006; King et al., 2008). However, the ability of an acquirer to adapt its technological knowledge to a target firm’s may influence its absorptive capacity (Cloodt, Hagedoorn, & Kranenburg, 2006; Colombo & Rabbiosi, 2014). As a result, including acquirer R&D in research models is important for acquisitions involving technology resources. Only examined in a handful of studies included acquirer R&D precluding its examination with financial performance measures, but it could be examined with innovative (patent) performance; however, we do not find a significant relationship between an acquiring firm’s prior R&D on innovative performance following an acquisition.

Acquirer debt

Acquiring firm access to debt provides a measure of an acquirer’s slack resources (Haleblian & Finkelstein, 1999); however, debt can also serve as a constraint after acquisition (Harford, 1999). Higher levels of debt for a firm are an indication of strategic risk for bankruptcy and debt increases the hurdle rate for further investment (Balakrishnan & Fox, 1993, Miller & Bromiley, 1990). For acquisitions, this is consistent with a problem of acquiring firm managers overestimating their ability to generate returns for an acquisition (hubris) and this may be worse for debt financing (Malmendier & Tate, 2008). In general, acquisition research expects better performance when an acquirer has a low debt to equity ratio (Hitt, Harrison, Ireland, & Best, 1998).

When aggregating research findings, we find conflicting results on the role of acquiring firm debt for different measures of acquisition performance. For short-term stock performance, acquiring firm debt displays a significantly positive correlation. This may reflect debt financing does not dilute firm ownership even though debt takes precedence over equity during bankruptcy. However, acquiring firm debt has a significantly negative relationship with accounting performance following an acquisition. Additional research examining firm acquiring firm debt and its relationship to acquisition performance is needed.

Prior acquisition experience

A prior meta-analysis (King et al., 2004) did not find a significant effect for acquisition experience at acquisition announcement. However, Hitt et al. (2001, p. 55) conclude: “the link between managerial experience and M&A success should not be underestimated.” Further, there is evidence that acquirers learn from acquisitions, but that firms may need diverse experience before knowing when prior experience applies (Haleblian & Finkelstein, 1999) to avoid superstitious learning or negative transfer-effects (Zollo, 2009). For example, learning from experience can help with selecting better targets (Hitt et al., 2009), or to develop superior human resource policies and practices (Nikandrou & Papalexandris, 2007). Still, a positive effect from experience requires active reflection on experience (Haleblian, Kim, & Rajagopalan, 2006) that can be hindered by completing acquisitions too frequently (Zorn, Sexton, Bhussar, & Lamont, 2017).

The Dunning-Kruger Effect (Kruger & Dunning, 1999) where novices display higher confidence than experts also likely plays a role in observations of a U-shaped impact of acquisition experience with performance (Arikan & McGahan, 2010). For firms inexperienced firms with acquisitions, manager confidence is likely low and they exercise greater mindfulness (Hutzschenreuter, Kleindienst & Schmitt, 2014), including using advisors to help avoid problems (Kim et al., 2011) that may help performance. However, as experience is gained, overconfidence likely leads to misapplication of experience as circumstances differ and managers lack perspective on what experience applies (Finkelstein & Haleblian, 2002). This refers to an inappropriate generalization error (Haleblian & Finkelstein, 1999) and it is consistent with findings that acquisition experience better applies when subsequent acquisitions are of similar size, in the same country, or in related industries (Ellis, Reus, Lamont, & Ranft, 2011; Muehlfeld, Sahib, & Van Witteloostuijn, 2012). Alternatively, false confidence can also make managers less sensitive to problems and increase the risk of overpaying for a target (Kim et al., 2011; Puranam et al., 2006), though this can be mitigated by having a diverse top management team (Nadolska & Barkema, 2014) or applying heuristics (Bingham, Eisenhardt, & Furr, 2007). Once sufficient diversity in experience is gained, confidence is regained and better decisions are made. For example, acquisition experience can become positive after an acquirer has made eight acquisitions (Haleblian & Finkelstein, 1999), suggesting multiple acquisitions are needed to know when prior experience applies to a given situation.

The articulation of experience through codification creates deliberate learning mechanisms that can also help build acquisition capabilities (Steigenberger, 2017, Trichterborn, Knyphausen-Aufseß, & Schweizer, 2016) and limit superstitious learning (Zollo, 2009). Recognition of being a “good” acquirer may have additional benefits from making it easier to acquirer and integrate companies (DiGeorgio, 2002). However, acquisition experience may be less important than the timing of an acquisition in a wave, as early acquirers experience better performance (McNamara, Haleblian, & Dykes, 2008). Further, it is likely necessary to also consider the acquisition experience of a target firm as it may improve their ability to negotiate and appropriate value from an acquirer (Cuypers et al., 2017), or contribute to integration problems (Zorn et al., 2017).

However, research draws on a range of measures on the relation between the prior number of acquisitions by an acquiring firm, regardless of how recent these experiences were (Colombo, Conca, Buongiorno, & Gnan, 2007). While Cuypers, Cuypers, and Martin (2017) measure acquisition experience over 10 years, experience is often capped at four years (e.g., Porrini, 2004; Reus & Lamont, 2009), and “forgetting” is infrequently modeled using the natural log of years passed (e.g., Ellis et al., 2011). Additionally, a target firm’s acquisition experience can mitigate advantages of acquirer experience (Cuypers et al., 2017). Experience also relates to international acquisitions (Dikova & Sahib, 2013; Muehlfeld et al., 2012) or target country experience (Basuil & Datta, 2015), and cross-border acquisitions are affected by similarities between acquisition events (Haleblian, & Finkelstein, 1999; Muehlfeld et al., 2012), regulatory change (Castellaneta & Conti, 2017), firm size (Laamanen & Keil, 2008), or whether prior experience involved a success (Muehlfeld et al., 2012).

In an updated meta-analysis, acquisition experience is significant and positively related to acquisition performance, but only for long-term measures of acquisition performance involving ROA for more than one year and managerial assessment. Still, acquisition experience is most often used in event studies around an announcement of an acquisition where aggregating results does not show a significant relationship. Acquisition experience may be a multi-dimensional construct and research does not consistently consider this potentiality. There is also a need to measure acquisition experience for greater lengths of time, and we recommend at least five years.

Method of payment

The use of stock, cash (debt) or a combination of both, or the method of payment for an acquisition is recognized as an important issue in M&A research (Tuch & O’Sullivan, 2007). For example, the method of payment for an acquisition has tax consequences with cash acquisitions representing a taxable event for target firms and stock acquisitions are taxable for an acquirer (Blackburn et al., 1997). Research largely assumes that managers pick the best method of payment for an acquisition (Arikan & Stulz, 2016; King et al., 2004), or that managers have better insight on a firm’s future stock price (Coff & Lee, 2003). As a result, there is an expectation that acquiring firm managers pay for an acquisition with stock when they believe the shares of their firm’s stock are overvalued (Rau & Vermaelen, 1998). As a result, stock financing for an acquisition presents a negative signal of acquiring firm value (Kaplan & Weisbach, 1992) that is associated with a negative market reaction (Carline, Linn, & Yadav, 2009; Moeller, Schlinge-mann, & Stulz, 2004).

Based on the preceding logic, confident acquirers pay for an acquisition using cash and experience better returns (Blackburn et al., 1997; Rappa-port & Sirower, 1999). Research provides some evidence that acquisitions paid with cash (debt) experience higher acquisition performance (Campbell, Sirmon, & Schijven, 2016; Linn & Switzer, 2001; McNamara et al., 2008; Tuch & O’Sullivan, 2007; Wong & O’Sullivan, 2001), and one reason may be that banks provide a monitoring role (Alderson & Betker, 2003; Jandik & Makhija, 2005). Still, using cash for acquisitions precludes returning it to shareholders (Jensen, 1986), and this has been associated with paying higher premiums that relate to an overestimation by managers (hubris) to improve returns from an acquisition (Harford, 1999; Malmendier & Tate, 2008; Wong & O’Sullivan, 2001).

Only a minority of researchers consider method of payment in empirical acquisition research, but when results are aggregated the method of payment is not a significant predictor of short-term stock market reaction. However, stock payment is significantly correlated with higher post-acquisition accounting performance. Establishing an explanation for the influence of method of payment for different measures of performance requires additional research.

Deal attitude

In general, research expects that acquisitions will perform better if an acquisition is friendly, or circumstances consistent with target firm management accepting an offer (Haspeslagh & Jemison, 1991). Friendly deals are more common (Jensen, 1993), but an exception is when there is a need to replace a target firm’s management (Healy, Palepu, & Ruback, 1997; Tuch & O’Sullivan, 2007). In these circumstances, a deal is considered hostile when a target firm rejects an acquisition bid and an acquirer uses a tender offer. During the 1980s, only 14 percent of U.S. acquisitions were hostile takeovers, and that is when they were arguably the most common (Andrade et al., 2001). Hostile acquisitions are less frequent outside the U.S. (Schneper & Guillen, 2004) with an estimate of less than one percent of acquisitions in the European Union involving hostile bids (Moschieri & Campa, 2009). While Harford (1999) finds no significant difference for deal attitude, other research supports a difference in performance with friendly deals associated with acquisition gains (Hitt et al., 1998) and hostile deals associated with losses (Moeller, Schlingemann, & Stulz, 2004; Wong & O’Sullivan, 2001). One reason involves greater information asymmetry in hostile acquisitions that makes due diligence more challenging (Cuypers et al., 2017; Harding & Rouse, 2007). However, only a limited number of studies consider deal attitude. In an updated meta-analysis, results could only be aggregated for short-term stock market performance, and results do not support a significant correlation.

Premium

Acquiring firms need to pay a premium to gain control of a target firm (Selden & Colvin, 2003; Wright, Renneboog, Simons, & Scholes, 2006), and this shares the benefits from an acquisition with target firm shareholders (Kummer & Steger, 2008; Sirower, 1997). While higher premiums reduce the benefits to an acquirer (Sirower, 1997), paying a premium does not necessarily lead to negative acquisition performance, even if premiums can exceed pre-deal stock prices by 30–50 percent (Laamanen, 2007). Instead, premiums vary widely and the amount of premium paid can reflect decision quality with high premiums associated with lower performance (Beckman & Haunschild, 2002; Haunschild, 1994; Hayward & Hambrick, 1997). Uncertainty in setting premium may also contribute to decisions influenced by anchoring. For example, comparable deals influence the premium paid for a target (Beckman & Haunschild, 2002; Malhotra et al., 2015), as does a target firm’s 52-week high (Berman, 2009). Higher premiums both increase pressure on management to increase returns from an acquisition at the same time it makes it more difficult (Krishnan, Hitt, & Park, 2007; Sirower, 1997).

Despite consistent justification of the importance of acquisition premium, only three recent empirical studies in management research include premium as a research variable. When the results are aggregated, higher premiums are significantly correlated with lower short-term stock market performance. Future research on acquisition performance needs to include premium as a control variable.

Acquirer size and relative size

Large firms typically make more acquisitions than smaller firms (Terlaak & King, 2007). Still, larger firms have advantages (slack resources) and disadvantages (inertia) toward acquisitions (King et al., 2003), as well as the combination of larger firms that increase managerial complexity (Shaver & Mezias, 2009). Large firms also may be more vulnerable to hubris associated with a greater likelihood of value destruction (Moeller et al., 2004). In contrast to large firm challenges, smaller acquirers experience more positive stock market reactions to acquisition announcements (Moeller et al., 2004).

However, size also reflects differences between an acquirer and its target. Integrating an acquisition where a target has a larger relative size to an acquirer displays increased complexity (e.g., Haspeslagh & Jemison, 1991; Ellis et al., 2011). For example, status differences with an acquisition of a smaller firm can facilitate integration (e.g., Devine, Lamont, & Harris, 2016), but it risks marginalizing target firm managers and employees (Chreim & Tafaghod, 2012). At the same time, combinations of firms of similar size experience more political behavior and conflict (Gomes, Angwin, Weber, & Yedidia Tarba, 2013). Reconciling different findings may involve a trade-off where a target firm needs to be large enough to effect an acquiring firm’s performance while keeping the integration challenges to a manageable level (King et al., 2008; Lamont, King, Maslach, Schwerdtfeger, & Tienari, 2018). Investigating curvilinear relationships between relative size and acquisition performance represents an opportunity for research.

When the impact of acquiring firm size on acquisition performance is aggregated, the results for acquiring firm size conflict for different measures of performance. For stock market reactions, larger acquirers can expect a significantly negative short-term stock market reaction. However, larger acquirers experience significant improvement in accounting performance (ROA), and managerial assessment of acquisition performance is also significantly higher for larger firms. The combined findings potentially suggest that larger firms develop acquisition capabilities. Meanwhile, meta-analysis finds relative size has a significantly negative correlation with short-term stock market measures of performance. Differences between findings on acquirer size and relative size suggest that these measures may reflect different constructs with acquirer size associated with acquisition capabilities and relative size associated with predicted integration difficulty.

Integration depth

At two extremes, target firm can be given autonomy or fully integrated (Birkinshaw et al., 2000; Haspeslagh & Jemison, 1991), and this reflects the depth of integration designed to unlock the value from making an acquisition (Cording et al., 2008; Puranam et al., 2006). At the very minimum, some level of integration necessary to realize synergies and to justify the premium paid (Shrivastava, 1986). Research on post-merger integration is consistent in stressing the importance of combining what needs to be integrated and avoiding the combination of what should not be integrated (Schweizer, 2005). While research generally considers autonomy and integration as distinct (Graebner et al., 2017), complementarity between an acquirer and target may require both integration and autonomy (Zaheer et al., 2013), suggesting the integration dimensions can coexist in one acquisition. This reflects a tension exemplified in high-technology acquisitions where desired knowledge is embedded in employees that are disrupted by acquisition integration (Ranft & Lord, 2002; Paruchuri et al., 2006), but integration is needed to access knowledge in a target firm. This paradox is consistent with the need for new integration strategies (Angwin & Meadows, 2015).

While autonomy limits an acquirer’s ability to improve performance (Eisenhardt & Santos, 2002; Lin, 2014), greater integration depth involves an increased amount of change (Bauer et al., 2016). The result is a tradeoff between greater disruption from a greater integration against higher long-term performance improvements (Chakrabarti & Mitchell, 2016; Lin, 2014b). Consistent with expectations of long-term gains, managerial assessment of performance displays a significant and positive correlation with integration depth in an updated meta-analysis. While objective measures of performance are unable to confirm this relationship, they do not provide insight into integration changes.

Integration speed

The time between acquisition completion and target firm integration defines integration speed (Cording et al., 2008; Shi, Sun, & Prescott, 2012), and research largely assumes a positive impact from integrating acquisitions quickly (e.g., Angwin, 2004; Cording et al., 2008). Advice for integration management stresses the need to act quickly before the willingness of employees to change deteriorates. This recognition coincides with often ambitious “first 100 days programs” for acquisition integration (Schweizer, 2005) to achieve improved cash flows (Sirower, 1997). However, the impact of integration speed is recognized as being more complex (Angwin, 2004; Bauer & Matzler, 2014), and research on speed of integration has not clearly identified when it improves or lowers acquisition performance (Homburg & Bucerius, 2006). For example, integrating a target firm too quickly risks destroying tacit capabilities that may have motivated an acquisition (Graebner, 2004; Ranft & Lord, 2002), as proceeding too quickly complicates coordination (Gaddis, 1987).

Reconciling different perspectives of integration speed may result from considering different dimensions of integration, such as task and human integration (Birkinshaw et al., 2000), that can proceed in parallel at different speeds (Bauer, 2015; Bauer et al., 2018; Meglio, King, & Risberg, 2017). For example, trust building needs time quick action may not work for human integration (Olie, 1990). Integration speed also needs to consider the amount of change (Bauer et al., 2016) with changes in both firms requiring more extensive communication and time (Ellis et al., 2012).

When research results are aggregated in meta-analysis, only managerial assessment of performance has been considered in conjunction with integration speed and it is not a significant predictor of acquisition performance. However, only four studies examined comparable research variables. Instead of concluding there is not a relationship, we agree with others that additional research is needed on integration speed and its different dimensions (Gomes et al., 2013; Homburg & Bucerius, 2006).

Employee turnover

Employee turnover is expected to be inversely correlated with acquisition success, as people stay when acquisitions work and they leave when they do not (Mayer & Kenney, 2004). While acquisitions motivated by cost savings include employee downsizing, actual turnover is often lower than initial intentions (Schweiger & Denisi, 1991) and the impact of turnover depends on the reaction of employees that survive lay-offs (Brocker et al., 1997). Still, low personnel turnover is generally considered to have a positive relationship with acquisition performance (Krishnan et al., 2007; Mayer & Kenney, 2004; Schweizer & Patzelt, 2012). One reason is that target firm managers experience disproportionately higher turnover following and acquisition (Krug & Shill, 2008), and this can have additional detrimental effects (Ellis et al., 2011; Graebner, 2004).

Further, the negative impact of turnover can be higher in service or knowledge industries where social capital losses exceed the benefits of cost savings (Eckardt, Skaggs, & Youndt, 2014; Hancock et al., 2013), as employee turnover represents a loss of knowledge (Schweizer & Patzelt, 2012). For example, a target firm’s top managers are often needed to help make sense of change following an acquisition for target firm middle managers and employees (Krishnan et al., 1997). One option to increase retention involves identifying managers or employees with complementary skills and target them with financial incentives (Brahma & Srivastava, 2007). Still, evidence suggests that financial incentives for retention may increase turnover as they are not sufficient for long-term loyalty (Ahammad, Glaister, Weber, & Tarba, 2012). Another option is to provide a target firm greater autonomy following an acquisition, but this can delay achieving the planned benefits from and acquisition. Only a handful of studies included common measures of employee turnover, and when results are aggregated, a significant correlation between employee turnover and accounting performance is not found.