Cross-border mergers and acquisitions: Impact on marketing capability and firm performance

Abstract

Emerging country firms have been increasingly engaging in cross-border mergers and acquisitions, and these acquirers predominantly acquire firms from developed countries. The motivation for such acquisitions is to achieve market access but also to benefit from transfers of cross-border managerial skills and knowledge. The performance of such acquisitions has started to receive some research attention, particularly financial performance, but the transfers to other areas such as marketing have not yet been explored. This article addresses this gap by studying the experience of 34 acquirers from emerging countries which acquired firms in developed countries. This study uses two-stage window data envelopment analysis (DEA) and Tobit regression to investigate the impact of these acquisitions on the marketing capability and overall firm performance of the acquiring firms. The results show that the marketing capability of the acquiring firms did improve in the post-merger years and this improvement can be partly attributed to the acquisition. The findings also show that the overall performance of the acquiring firms improved following acquisition, but this is a continuation of superior performance from the pre-merger years rather than a synergistic gain from the acquisitions.

Keywords

cross-border M&A data envelopment analysis (DEA)emerging markets firm performance marketing capability

Introduction

Research has shown that mergers and acquisitions (M&As) come in waves and five major waves occurred over the 20th century (Martynova and Renneboog, 2008). A sixth wave occurred during the period from 2002 to 2007 and was part of the economic boom that precipitated the global financial crisis in 2008 (Alexandridis et al., 2012). This recent wave was quite different from earlier waves in a number of respects, one of which was the increasing rate of cross-border M&As. Unlike national mergers, the merging partners in cross-border M&As are based in two different countries. In particular, the sixth wave saw a significant increase in the participation of firms from emerging countries in M&A transactions (Martynova and Renneboog, 2008). In 2004, the value of cross-border M&A by emerging country firms stood at US$37 billion; this skyrocketed to US$182 billion in 2008 – an increase of 392% (UNCTAD, 2009). In 2009 the value of M&As originating from emerging markets exceeded that in developed markets for the first time (Bhagat et al., 2011; Aybar and Thanakijsombat).

According to a report by Boston Consulting Group (2006), the top 100 firms from various emerging countries are expanding globally in a wide array of industries such as industrial goods, pharmaceuticals and telecommunications, and this global expansion is mainly happening through cross-border M&As. This report showed further that 57% of the cross-border M&A deals made by these emerging-country firms from 1985 to 2005 involved target firms from developed countries (emerging to developed). Some of the major acquisitions by emerging country firms in those years include Chinese automotive company Geely’s acquisition of Volvo, Indian automotive firm Tata Motor’s acquisition of Jaguar and Land Rover, Mexico-based Cemex’s US$15.1 billion acquisition of Australia’s Rinker Group and most recently, Chinese firm Lenovo’s acquisition of Motorola for US$ 2.9 billion.

M&A research in a developed country context has found that firms make acquisitions for various reasons which may be summarized as pursuit of economies of scale, economies of scope and market power (Haleblian et al., 2009; Seth, 1990). It appears therefore that firms in developed countries engage in M&A to capitalize on their existing competitive advantage and that the transfer of benefits following acquisition would be mainly from acquirer to target. This is exactly the pattern that was found in research by Capron (1999) and Capron and Hulland (1999); they found that most of the flow of marketing resources went from acquirers to target firms.

In contrast, research has shown that emerging-country firms suffer from significant competitive disadvantages vis-à-vis firms from developed countries. These competitive disadvantages arise from lack of knowledge about overseas markets, lack of internationally known brands, outdated technology, difficulty accessing distribution, and many others (Child and Rodrigues, 2005). It appears likely, therefore, that the motives of emerging-market firms for entering into M&A deals are the opposite of developed-market firms. In other words, they are seeking to reduce their competitive disadvantage rather than to leverage a competitive advantage. The scant research on M&A in an emerging-country context has tended to bear this out; it has shown that firms from emerging countries acquire firms from developed countries to acquire strategic assets such as technological capability, brand assets, and market access and capabilities, with the objective of reducing their competitive disadvantage (Child and Rodrigues, 2005; Deng, 2009; Rui and Yip, 2008).

Acquisition of new strategic assets, however, does not guarantee the reduction of competitive disadvantage. Research has shown that successful integration following acquisition largely determines the extent to which an acquisition benefits the acquiring firm in developed markets (Homburg and Bucerius, 2005; Tarba and Weber, 2011). Thus far, nothing has been written in the academic literature on whether or how these newly acquired strategic assets help emerging-market firms to reduce their competitive disadvantage. Moreover, the impact of these strategic assets on the marketing capability of the emerging-market firms in the post-merger years also remains unexplored.

This study attempted to fill this lacuna in the literature based on the premise that one of the motivations of emerging market firms for engaging in cross-border M&A is to attain marketing assets such as strong brands, market access and customer relationships, as well as marketing/brand management expertise. These benefits may be summarized under the general title of ‘marketing capability’. The study reported in this article attempts to measure the extent to which marketing capability is actually influenced by acquisitions, either positively or negatively, and especially to assess the effect of acquisitions of developed country firms on the performance of acquirers from emerging markets.

The article is organised as follows. The first section reviews the relevant literature on motives for M&As, and post-merger financial performance. The next section identifies the hypotheses tested in this study. The third section describes the data and methodology used in this study, and the fourth section reports the findings. The article concludes with suggestions for future research.

Literature review: Background of the study

Motives for M&As

The motives for M&As have been studied extensively in a developed country context, and within various disciplines, including finance, accounting, organization studies and management (Hannan and Pilloff, 2009; Martynova and Renneboog, 2008; Trautwein, 1990; Tuch and O’Sullivan, 2007). These studies broadly classified merger motives into value creating and value destroying motives (Haleblian et al., 2009). Value creating motives include such things as pursuit of market power, exploitation of synergies, resource deployment and resource dependence, and these have been conceptualized and investigated mainly by management and organization scholars (Ambrosini et al., 2011; Haleblian et al., 2009). Value destroying merger motives include such things as managerial hubris and increased CEO compensation which have been studied mainly by finance scholars (Haleblian et al., 2009; Martynova and Renneboog, 2008).

In contrast, only a handful of studies have investigated the motives of emerging-market firms for engaging in cross-border M&As (e.g. Child and Rodrigues, 2005, Deng, 2009). However, those few studies indicate that their motives for acquisitions are different from those of acquirers from developed countries (Child and Rodrigues, 2005; Deng, 2009; Rui and Yip, 2008; Vu et al., 2009). Broadly speaking, the two main motivations of emerging country firms for acquiring foreign firms are strategic resource seeking and fast entry to foreign markets. For example, it has been found that Chinese and Indian firms engage in cross-border M&As mainly to acquire strategic assets such as natural resources, superior managerial skills and knowledge-based capabilities such as marketing and brand building capabilities (Nicholson and Salaber, 2013).

It appears therefore that merger motives vary from developed countries to emerging countries. While developed-market firms engage in M&A predominantly to utilize their competitive advantage, firms from emerging-markets acquire firms in developed-markets with a view to acquiring strategic assets, thereby lessening their competitive disadvantage.

M&A and value creation

Value is perceived as an anticipated outcome of any sort of planned and organized activity. In the context of M&As, performance is usually defined as the amount of value created as a result of combining the firms involved (King et al., 2004), and the concept of value creation is synonymous with that of synergy: the 2 + 2 = 5 effect (Seth, 1990). Several theories have been put forward concerning how cross-border M&A might affect the value of the combined firms (Bertrand and Betschinger, 2012; Lebedev et al., 2015; Nicholson and Salaber, 2013). Some authors have posited that M&A might lead to enhanced efficiency of the combined firms in various aspects of operations such as marketing. These studies argue that firms should be able to enhance operational efficiency through achievement of economies of scale, economies of scope, improved capacity utilization and learning economies (Bertrand and Betschinger, 2012).

According to resource-dependence theory, firms from emerging markets might acquire firms from developed countries to acquire strategic assets and skills such as strong brands, access to markets and distribution channels, and established customer relationships leading to an enhancement of their overall marketing capability (Capron and Hulland, 1999; Deng and Yang, 2015). Capron and Hulland (1999) have shown that acquiring companies in developed markets tend to transfer their assets and capabilities to firms they have acquired to enhance their operational performance, leading to an improvement in overall performance for the combined entities. In the case of emerging country acquirers, the expectation would be that the flow of benefits would be in the opposite direction, from target to acquirer.

A number of studies have shown that the realization of such gains can be hindered by unsuccessful integration of the two firms following M&A (Deng, 2010; Homburg and Bucerius, 2005; Lebedev et al., 2015; Shimizu et al., 2004). It has been shown that successful redeployment of assets and skills between the merging firms depends upon the extent to which the target and acquiring firms have been integrated (Capron and Hulland, 1999; Homburg and Bucerius, 2005). The successful redeployment of strategic assets such as marketing knowledge from the target firm to the acquirer also hinges upon the absorptive capacity of the acquiring firm (Deng, 2010; Liu and Woywode, 2013). This absorptive capacity is something that may not be counted upon in firms from emerging countries with different cultural and economic backgrounds.

Cultural disparity between the merging firms has been identified as a possible hindrance to successful integration following M&A and has received extensive research attention, although with mixed results (Chakrabarti et al., 2009; Datta, 1991). Moreover, following acquisition of a developed country firm, emerging market firms have to learn how to do business in a new environment with many unfamiliar challenges – economic, legal, administrative and cultural (Bertrand and Betschinger, 2012). How quickly these emerging market firms can get to understand the new business environment as well as the new cross-border stakeholders will be dependent upon their organizational learning capability, and one important dimension of this is marketing capability (Dikova et al., 2010).

Financial performance following cross-border M&A

Post-merger financial performance has received attention from several different disciplines including accounting, finance, management, economics and industrial organization (Zollo and Meier, 2008). Most of these studies have been conducted in developed countries. The two most common perspectives taken by these studies are the shareholder perspective, measuring returns based on share value and the accounting perspective, measuring operating performance. Despite the extensive volume of research and the variety of the methodologies applied, the evidence is extremely mixed, with the general tendency towards a negative view of post-merger performance (King et al., 2004; Tuch and O’Sullivan, 2007).

The number of studies conducted on emerging country acquirers is very meagre compared to the vast number conducted on developed country acquirers, and the results of the few studies that there are, are inconclusive (Bhagat et al., 2011). On the positive side, Boateng et al. (2008) found that cross-border acquisitions by Chinese acquiring firms had a positive impact on shareholder wealth, in a study of 27 cross-border acquisitions between 2000 and 2004. A study of 425 cross-border acquisitions by Indian firms from 2000 to 2007 also found that they generated significant abnormal returns for the shareholders (Gubbi et al., 2010). Another large study of 698 cross-border acquisitions by emerging country firms from 1991 to 2008, also demonstrated that the acquirers experienced a positive and a significant market response on the announcement day (Bhagat et al., 2011). Similarly, Nicholson and Salaber (2013) found that acquiring firms earned abnormal returns in a study of Chinese and Indian companies from 2000 to 2010.

On the negative side, however, Aybar and Ficici (2009) found that the announcements of acquisitions were associated with negative abnormal returns in a study of 58 firms from emerging countries that had made 433 cross-border acquisitions from 1991 to 2004. They concluded that this was because the potential benefits expected from cross-border acquisitions were offset by various integration costs. Likewise, Chen and Young (2010) found that Chinese acquiring firms with majority government ownership destroyed shareholder value in a study of the post-merger performance of 39 firms that made cross-border acquisitions between 2000 and 2008. Bertrand and Betschinger (2012) also found that the profitability of Russian acquirers (earnings before interest and tax (EBIT) over total assets) declined following acquisitions, based on a study of 120 cross-border acquisitions by 92 firms.

It appears, therefore, that the evidence is fairly evenly split between the positive and negative, with no consensus as to whether acquisitions of firms in developed countries by firms from emerging countries actually benefit the acquirers or the combined entities. These studies focused on financial performance as their dependent variable, with most using stock market performance as their measurement, while only a handful of studies used operating performance. None of these studies got behind the financial performance, however, to see which functions or operations or teams contributed to the final performance outcome. In particular, none of these studies considered how the acquisition of firms in developed countries impacted the marketing assets or capabilities of the acquiring firms from emerging markets.

Marketing capability in a cross-border M&A context

To conceptualize marketing capability, we have relied on the resource-based view (RBV) of the firm (Barney, 1991), extended by reference to the dynamic capabilities (DC) theory of organizations (Teece et al., 1997). According to this view, the marketing capability of a firm may be seen as part of its overall dynamic capabilities as an organization. As an extension of the RBV theory, Teece et al. (1997) coined the term ‘dynamic capabilities’, based on three interrelated concepts, which are ‘process, position and path’. The ‘process’ here is applied to the overall strategic decision-making and day-to-day operational execution processes of a firm. The ‘position’ refers to all of the firm’s physical, human and organizational resources, actual and potential, and the firm’s capacity to source and integrate/re-integrate resources in a competitive business environment to achieve its strategic goal(s). The term ‘path’ indicates the firm’s strategic direction that it has followed so far and/or would follow in the future (Teece et al., 1997).

In keeping with the dynamic capabilities theory, marketing capability has been defined ‘as the integrative process by which a firm uses its tangible and intangible resources to understand complex consumer needs, deliver product differentiation relative to competition and achieve superior brand equity (Nath et al., 2010)’. Tangible resources include infrastructure such as factories, warehouses and distribution systems as well as materials, inventory and marketing collateral. A firm combines these tangible resources with intangible resources such as the expertise and know-how of its employees to develop and sustain its brands and communication and customer relationships, all part of its marketing capabilities (Vorhies and Morgan, 2005). A strong marketing capability in turn increases its ability to generate innovative products and services that might further enhance its financial performance into the future (Dutta et al., 1999; Nath et al., 2010; Vorhies and Morgan, 2005).

Capron and Hulland (1999) investigated the degree of redeployment of three marketing resources – brands, sales forces and general marketing expertise (GME) – across merging firms following horizontal acquisitions in developed markets. Brands and sales forces are examples of tangible assets, while GME is an intangible asset, that is, it is responsible for building and managing relationships between the firm, its brands and external stakeholders, including distributors, retailers and end customers (Capron and Hulland, 1999).

GME refers to knowledge of the market and business practices related to the development and implementation of marketing strategy. GME is an intangible, ‘intellectual’ or ‘knowledge-based’ resource, known as a capability in the literature (e.g. Sanchez et al., 1996). It may be thought of as a familiarity or insight into the behaviour of the market that is often called ‘market sensing’. Companies try to develop and improve their ‘market-sensing’ ability by spending more resources to interact with existing and potential customers (Dutta et al., 1999). Increased market-sensing capability leads to better understating of the customers, competitors’ strategy as well as about the marketplace (Foley and Fahy, 2004) leading to an increase in competitive advantage (Nath et al., 2010).

Companies combine the expertise and know-how of their employees with their brand assets and sales resources to develop and sustain marketing capabilities (Vorhies and Morgan, 2005).

From an accounting point of view, they represent an intangible asset (Capron and Hulland, 1999; Srivastava et al., 2001), and that is how we measured them for our study. We used intangible assets as a proxy for brand equity, and we used the level of receivables as a proxy for the amount of resources invested in customer relationships.

To summarize the discussion above, it appears that emerging market firms acquire firms in developed markets in the hope of acquiring market access, as well as strategic assets and know-how to enable them to compete successfully in those markets (Bertrand and Betschinger, 2012). This logic leads to the general proposition that the flow of resources’ post-acquisition is likely to be predominantly from target to acquirer, rather than the reverse. Marketing capability is one key strategic asset that ought to be subject to such a transfer, leading to the proposition that cross-border acquisitions by firms from emerging countries should lead to an increase in marketing capability and, thereby, to an improvement in overall firm financial performance. In view of the foregoing, the following hypotheses are proposed:

H₁: The marketing capability of emerging country firms will be improved following acquisition of a firm from a developed country.

H₂ : The overall financial performance of the emerging country firms is likely to improve following acquisition of a firm from a developed country.

Methodology

Design of the study

The purpose of this study is to examine the impact of acquisitions on marketing capability, as well as on overall firm performance, so a longitudinal study of pre- and post-measures was necessary to facilitate detection of any improvement or deterioration in performance after the acquisition. This study used a two-stage data envelopment analysis (DEA), as well as DEA window analysis to investigate the impact of cross-border acquisitions on marketing capability and firm financial performance.

Sample size and sample selection

The context of this research was on cross-border M&As in which the acquiring firms come from emerging countries and the target firms come from developed countries, as defined by the Dow Jones country classification system. Among the emerging markets, this study focused only on the BRICS countries – Brazil, Russia, India, China and South Africa, since companies from these countries are the most active in cross-border M&A.

M&As are complex phenomena so it was essential to rule out the impact of extraneous variables that might potentially confound the results, so as to be able to isolate the effect of the acquisition transaction on the sample firms. Following similar studies (e.g. Campa and Hernando, 2006; Healy et al., 1997), this research used a number of sample selection criteria to construct a clean sample, to enable us to detect a change in marketing efficiency between pre- and post-merger years. The criteria for sampling were:

the acquiring firm had to be located in one of the BRICS countries and the target firm had to be located in a developed country;

the sample period was restricted to the years 2000–2012, because emerging market firms have been most active in cross-border M&A during this period;

the study focused only on non-financial firms from a range of other industries. This was driven by the fact that accounting reporting standards and procedures vary considerably between financial and non-financial firms making them difficult to compare;

both the target and acquiring firms had to be public companies so that data on the input and output variables were publicly available;

data pertaining to input and output variables for both the target and acquiring firms had to be available for 2 years before and 2 years after the acquisition to enable tracking of the pre- and post-performance;

the acquirer had to acquire full ownership (100% acquisition) of the target company so as to have complete control over the company’s future strategy.

Based on these criteria, we identified 34 acquisitions which became the sample for this study. The sample size was dictated by the need to obtain detailed data on both companies involved in each deal, which required extensive study of published records, and considerable manual data collection. It is worth noting that it is difficult to collect data on cross-border acquisitions carried out by firms from emerging countries (Bhagat et al., 2011). Nonetheless, this sample size is consistent with previous M&A studies (e.g. Boateng et al., 2008; Liu and Woywode, 2013). Moreover, utilization of DEA windows analysis allowed this study to increase the sample size to a total of 136 firm-year observations (34 firms × 4 years).

Data sources and data collection

Data collection was carried out in two phases. In the first phase, data pertaining to M&A deals, such as deal year and deal value, were collected. Subsequently, data were collected on all input and output variables pertaining to each of the M&A deals selected in the first phase.

In the first phase, all M&A deal-related data were collected from Thomson One Banker database. Thomson One Banker database is a comprehensive database for global M&As which contains information on a wide variety of industries and has been used extensively by earlier studies on M&A (e.g. Rahman et al., 2016).

In the second phase, data relating to all input and output variables were collected from COMPUSTAT which is a widely used database for company financials (e.g. Ghosh, 2001). Data were collected for the 2 years before and after the merger for the selected sample firms. Since most of the sample firms report their accounting data in local currency, data for all input and output variables were converted to US dollars to facilitate comparison across firms and across countries. We used the yearly average exchange rate between US dollar and the other relevant currencies from www.xe.com for currency conversion.

Data envelopment analysis

Since the first use by Charnes et al. (1978), DEA has grown in popularity among many academic disciplines as a strong non-parametric, linear programming tool to measure efficiency of decision-making units (DMUs) within a given population involving multiple inputs and outputs (Cook and Seiford, 2009; Emrouznejad et al., 2008; Seiford, 1996). DMUs can be any set of entities that transform comparable inputs into comparable outputs. Examples of DMUs include schools, banks, and so on (Thomas et al., 1998).

Unlike regression which focuses on central tendency and is unable to include multiple inputs and outputs, DEA focuses on efficient frontiers and can incorporate multiple inputs and outputs to measure efficiency (Ahn and Le, 2014; Banker et al., 1984). Hence, DEA has proved to be a useful tool to measure relative efficiency by comparing the efficiency score achieved by one DMU with the efficiency scores of other DMUs (Emrouznejad et al., 2008; Seiford, 1996). DEA measures the DMU’s relative efficiency score by determining the minimum possible inputs needed to produce a set of outputs, or by determining the maximum possible outputs that can be produced from a given set of inputs. It also identifies the best practice frontier or data envelope (Wang et al., 2010).

The ratio of weighted inputs and outputs produces a single efficiency value known as the relative efficiency. DMUs with a ratio of 1 are considered to be efficient, given the required inputs and outputs produced. The DMUs with a ratio of less than 1 are less efficient compared to the most efficient DMUs. Furthermore, DEA provides a well-defined relationship between the inputs and outputs used by a DMU (Donthu et al., 2005; Seiford, 1996).

DEA window analysis

Most of the extant studies in marketing using DEA analysed cross-sectional data, wherein each DMU was observed only once. However, data on DMUs are often available over a span of time and, in such cases, the efficiency score may be measured for each time period, making it possible to detect and compare the efficiency of DMUs over multiple time periods (Asmild et al., 2004; Webb, 2003). In such cases, each time period for each DMU is treated as if it were a distinct DMU. This DEA technique is known as ‘window analysis’ (Fadzlan, 2007; Kao and Liu, 2014), and this was utilised in our study since the objective was to compare marketing capability as well as overall firm performance between pre-merger and post-merger years. Using DEA window analysis, this study computed and compared the marketing capability and overall firm performance of each of the DMUs in the sample for the pre-merger as well as post-merger years.

Two-stage DEA

Most research employing DEA analysis has used the single-stage model which only considers a one-dimensional relationship between input and output variables (Wang et al., 2010). The DEA literature shows that one-stage DEA is relatively strong for analysing performance, but the two-stage DEA analysis can more precisely measure and differentiate between the efficiency of resource use and the effectiveness of the output generated (Wang et al., 2010). The results of two-stage DEA analysis are more conclusive, therefore, and can better help management detect areas for potential improvement (Wang et al., 2010). This is the model used in this study.

Types of DEA model and orientation

Various types of DEA models have been proposed and tested (Ahn and Min, 2014). Two of the most popular and widely used are the CCR and BCC models. Charnes et al. (1978) developed the CCR model which assumes constant returns to scale (CRS), and Banker et al. (1984) introduced the BCC model which assumes variable returns to scale. This research used the CRS model to measure marketing capability and firm performance.

DEA models can be either input-oriented or output-oriented. While an input-oriented DEA model aims to minimise the use of inputs while maintaining the same level of outputs, an output-oriented model aims to maximise the level of outputs given the current level of inputs. In other words, an output orientation assumes that DMUs have direct control over the outputs and an input orientation assumes little control over the outputs (Ahn and Min, 2014; Harris et al., 2000). As firms in an M&A deal cannot directly control outputs such as sales or profit performance, this research adopted an input-oriented model.

Measurement and operationalization of input and output variables

The input and output variables used for the measurement of marketing capability and firm performance were chosen in line with similar studies, to maintain consistency and comparability. This study followed the input and output variables used by Nath et al. (2010) for the measurement of marketing capability, with some modification. We used three inputs to measure marketing capability: marketing expenditure, intangible assets and relationship expenditure (Nath et al., 2010). Sales performance is the most common measure of marketing outputs, and we used sales as our core output measure, also in line with Nath et al. (2010). However, we used an additional sales-related variable as an output variable for the measurement of marketing capability, namely, inventory turnover, as an indication of the momentum of sales over time, as suggested by Gaur et al. (2005). Finally, to operationalise firm performance, this study followed Saranga and Moser (2010), measuring profitability as EBIT, divided by total sales revenue. Table 1 summarizes the input and output variables used in the two-stages of the study.

Table 1.

Inputs and outputs for DEA.

Input variables (first stage)	Description	Operationalization
	Brand equity	Monetary value of intangible assets
	Customer relationship expenditure	Yearly dollar amount of accounts receivables
	Marketing expenditure	Sales, general and administrative expenses
Output variables (first stage)	Sales	Sales turnover
Output variables (first stage)	Inventory turnover	Cost of goods sold divided by total inventory
Output variable (second stage)	Firm performance	EBIT divided by total revenue

DEA: data envelopment analysis; EBIT: earnings before interest and tax.

As this study is longitudinal in nature, the DEA window analysis facilitated detection of any change in marketing capability and firm performance over time, pre-merger and post-merger. Figure 1 illustrates the progression of two-stage DEA with window analysis.

Figure 1.

DEA two-sage window analysis evaluation process. DEA: data envelopment analysis.

Using a combination of window analysis and two-stage DEA, this study computed the marketing capability as well as the financial performance for each of the 2 years before and after the merger. Since there were two firms before the acquisition, that is, the acquirer and target firms, we calculated pro forma values for each of the input and output variables for the combined firms during the pre-merger years based on the sum of the actual values of the two firms. This approach was consistent with previous studies (e.g. Ghosh, 2001; Sharma and Ho, 2002). Also consistent with previous studies (e.g. Healy et al., 1992), we aggregated the pre-acquisition data for each of the input and output variables for both the acquiring and acquired firms to compute the yearly aggregate for the combined firms.

Findings of the study

Descriptive statistics and paired-sample t-test

Table 1A (Appendix) shows the distribution of M&A deals between the acquirer and target countries. Table 2 reports the descriptive statistics for the input and output variables utilised in this study. As a preliminary investigation into how the values of these input and output variables changed between the pre- and post-merger years, a paired sample t-test was carried out, the results of which are reported in panel B of Table 2. Rather than arbitrarily selecting one pre- and post-merger year to detect any change in the values of the input and output variables, the mean of the pre-merger and post-merger years was computed and compared to detect any change.

Table 2.

Descriptive statistics and paired sample t-test.

Panel A. Descriptive statistics: mean of inputs and outputs (in USD million except inventory turnover and EBIT margin)
Input and output variables	Pre-merger year (t − 2)	Pre-merger year (t − 1)	Post-merger year (t + 1)	Post-merger year (t + 2)
Brand equity	127.356	383.17	941.66	898.44
Customer relationship expenditure	751.70	851.02	1080.68	1209.83
Marketing expenditure	413.43	508.37	714.48	826.86
Sales	4414.27	5636.71	7339.87	7638.35
Inventory turnover	6.49	6.79	5.71	5.82
Firm performance (EBIT margin) (%)	17.5	20	18	−6.5
Panel B. Results of paired sample t-test.
Input and output variable		Pre-merger mean	Post-merger mean	T (sig)
Brand equity		255.26	920.05	−2.76 (.009)
Customer relationship expenditure		801.36	1145.25	−2.736 (.01)
Marketing expenditure		460.90	770.67	−3.60 (.001)
Sales		5025.49	7489.11	−2.66 (.01)
Inventory turnover		6.64	5.77	1.99 (.05)
Firm performance (EBIT margin)		19%	6%	1.09 (.28)

Note: Sig are the p values.

EBIT: earnings before interest and tax.

The results show that the values for brand equity, customer relationship expenditure, marketing expenditure and sales increased in the post-merger years compared to the pre-merger years and these changes are statistically significant. In other words, the value of marketing inputs increased for the combined firms following merger, indicating a commitment to increased investment. Curiously, however, inventory turnover and EBIT declined in the post-merger years, although the decline in EBIT is not statistically significant.

First-stage DEA window analysis: Marketing capability in pre- and post-merger years

Table 2A (Appendix) shows the detailed results of the window analysis of the marketing capability scores for the pre-and post-merger years for each firm. It is notable that window width was set at 1. Table 3 summarizes the results of the DEA window analysis of marketing capability for the first stage. While the number of efficient and inefficient DMUs remained fairly consistent in the pre-merger and post-merger years, results show that the mean marketing capability scores improved following the M&A. In other words, the marketing capability score of all sample firms for the post-merger years is higher, on average, compared with the pre-merger marketing capability score.

Table 3.

Marketing capability under the CRS model, DEA window analysis (first stage).

	Marketing capability score
	Pre-merger years		Post-merger years
	t − 2	t − 1	t + 1	t + 2
Mean	0.4074	0.4351	0.4604	0.6262
Standard deviation	0.2951	0.2701	0.2771	0.2880
Minimum	0.11	0.14	0.12	0.04
Maximum	1	1	1	1
Number of efficient DMUs (M&As)	6	5	5	7
Number of inefficient DMUs (M&As)	28	29	29	27

DEA: data envelopment analysis; CRS: constant returns to scale; DMU: decision-making unit; M&A: merger and acquisition.

It is important to note that DEA window analysis is unable to detect statistically significant differences in marketing capability scores between the pre-merger and post-merger years. Hence, to test our hypothesis (H₁), as well as to investigate the extent to which post-merger marketing capability was actually influenced by the merger itself rather than being a continuation of pre-merger marketing capability, we examined marketing capability using the intercept model first used by Healy et al. (1992), and subsequently by other studies measuring post-merger performance (Powell and Stark, 2005; Sharma and Ho, 2002). We conducted a regression as follows:

{MarketingCapability}_{post} = α + β {MarketingCapability}_{Pre} + ε

The slope coefficient β measures the persistence in marketing capability. In other words, β measures the extent to which post-merger marketing capability is a continuation of the pre-merger marketing capability rather than a step change. A significant β will indicate persistence of pre-merger marketing capability into the post-acquisition period. The intercept (α) coefficient captures the acquisition-induced improvement or deterioration in marketing capability. In other words, the intercept (α) which is independent of the pre-merger marketing capability should indicate the extent to which post-merger marketing capability is a function of the acquisition. These interpretations follow Healy et al. (1992).

We used Tobit regression which is also known as censored regression model for this purpose. Tobit regression is used when there is either left- or right-censoring in the dependent variable (also known as censoring from below and above, respectively). Since the marketing capability value derived from DEA ranges between 0 and 1 (double censored), Tobit regression is the most appropriate (Laursen and Salter, 2006). Table 4 shows the results of the Tobit regression.

Table 4.

Results of Tobit regression.

	Post-merger marketing capability coefficient
Constant (α)	0.1947503***
Pre-merger marketing capability	0.8495756***
Number of observations	34
Number of left-censored observations	0
Number of right-censored observations	3
Log likelihood	13.660847
Chi-square	43.17***
Pseudo R ²	2.7240

***p < 0.01.

The results of the Tobit regression (Table 4) demonstrate that the constant (α) coefficient is statistically significant which implies M&As have a positive impact on the marketing capability of the emerging market firms. Furthermore, the coefficient (β) for pre-merger marketing capability also turned out to be statistically significant which indicates that pre-merger marketing capability also contributed to the improved post-merger marketing capability. In other words, post-merger marketing capability is a continuation of the pre-merger marketing capability.

In sum, our results demonstrate that the improvement of marketing capability of the emerging market firms in the post-acquisition years is the combined effect of pre-merger marketing capability as well as of the merger itself. Therefore, our hypothesis (H₁) that the marketing capability of emerging country firms will be improved following acquisition of a firm from a developed country is partially supported.

Second-stage DEA window analysis: Firm performance in pre- and post-merger years

Table 3A (Appendix) shows the detailed results of window analysis for the overall financial performance for the pre-and post-merger years for each firm. As explained in the ‘Methodology’ section, the output variables, namely, sales and inventory turnover, used in the first stage of the DEA have been used as the input variables for the second stage of analysis and the EBIT margin has been used as the final output variable. In other words, the second stage of the DEA window analysis calculated overall firm performance for the pre- and post-merger years by incorporating sales and inventory turnover as inputs and EBIT divided by total revenue as the output variable. Table 5 summarises the results of the second stage of the DEA window analysis on the impact of acquisitions on firm financial performance.

Table 5.

DEA window analysis (second stage) M&A and firm performance.

	Firm performance
	Pre-merger years		Post-merger years
	t − 2	t − 1	t + 1	t + 2
Mean	0.2562	0.2931	0.3717	0.3815
Standard deviation	0.2930	0.3459	0.3736	0.3817
Minimum	0.01	0.00	0.00	0.00
Maximum	1	1	1	1
Number of efficient DMUs (M&As)	3	5	7	6
Number of inefficient DMUs (M&As)	31	29	27	28

DEA: data envelopment analysis; DMU: decision-making unit; M&A: merger and acquisition.

The results show that the mean scores for overall financial performance improved following the acquisition. However, as DEA window analysis is unable to detect any statistically significant difference for overall firm performance between the pre- and post-merger years, we again used the intercept model (Healy et al., 1992) as was done for marketing capability in the last section. To test our second hypothesis (H₂) and to investigate the extent to which post-merger firm performance was actually influenced by the merger itself rather than representing a continuation of pre-merger performance, we examined overall firm performance using the intercept model (Healy et al., 1992; Powell and Stark, 2005; Sharma and Ho, 2002). We conducted a Tobit regression analysis (Laursen and Salter, 2006), as follows

{FirmPerformance}_{post} = α + β {FirmPerformance}_{Pre} + ε

The slope coefficient β measures the persistence in firm performance. In other words, β measures the extent to which post-merger firm performance is a continuation of the pre-merger firm performance rather than a step change in performance. A significant β will indicate persistence of pre-merger firm performance into the post-acquisition period. The intercept (α) coefficient captures the acquisition-induced improvement or deterioration in firm performance. Put differently, the intercept (α) which is independent of the pre-merger firm performance should indicate the extent to which post-merger firm performance is a function of the acquisition.

The results of Tobit regression (Table 6) demonstrate that the constant (α) coefficient is statistically insignificant which implies that M&As have no impact on the overall firm performance of the emerging market firms. Therefore, our second hypothesis (H₂) is not supported. Furthermore, the coefficient (β) for pre-merger firm performance turned out to be statistically significant which indicates that pre-merger firm performance contributed to the improved post-merger firm performance. In other words, overall firm performance post-merger is a continuation of pre-merger performance and does not display any special increment as a result of the acquisition.

Table 6.

Results of Tobit regression.

	Post-merger firm performance coefficient
Constant (α)	0.0865102
Pre-merger firm performance	1.185254***
Number of observations	34
Number of left-censored observations	0
Number of right-censored observations	5
Log likelihood	−4.4652664
Chi-square	32.94***
Pseudo R ²	0.7867

***p < 0.01.

Discussion and conclusions

M&A research in an emerging-country context has shown that firms from emerging countries acquire firms from developed countries to acquire strategic assets such as technological capability, brand assets and marketing capability with the apparent objective of reducing their competitive disadvantage and, by implication, enhancing their overall firm performance (Child and Rodrigues, 2005; Deng, 2009; Rui and Yip, 2008). The findings reported in this article sought to extend this line of research by investigating whether acquisitions by emerging market firms of firms from developed markets actually achieve these objectives. In particular, this study set out to examine whether emerging market firms could enhance their marketing capability following acquisition of firms from developed countries. A second objective of this research was to examine the impact of M&A on overall firm performance.

This study gathered a multi-industry sample of 34 acquisitions by emerging market firms of firms in developed markets, that is, a paired sample of 68 individual firms. We used a two-stage DEA window analysis that enabled us to conduct a longitudinal analysis over a 4-year time period, including 2 years before the acquisition and 2 years after it. This method of analysis is novel in marketing research but seemed to offer significant advantages for our particular purpose. It enabled us to compare data over multiple time periods, a longitudinal approach which is significantly better than previous studies which were mostly cross-sectional and only able to compare single data points. Furthermore, the two-stage DEA analysis used in this study can differentiate between the efficiency of resource use and the effectiveness of the output generated. The results of two-stage DEA are more conclusive, therefore, and can better help management detect areas for potential improvement.

Our evidence suggested that firms were indeed able to enhance their marketing capability through acquisitions. In other words, acquiring firms from emerging markets gained a significant benefit from access to the skills and resources of the firms they acquired in developed markets. However, our results also suggest that the improvement in marketing capability in the post-acquisitions years was partly a continuation from the pre-merger years. In other words, firms that had strong marketing capabilities pre-merger tended to remain strong after the acquisition. Therefore, our hypothesis (H₁) that the marketing capability of emerging country firms will be improved following acquisition of a firm from a developed country is partially supported.

This evidence of a momentum effect was also evident in our results on overall firm performance. Our results showed that overall firm performance of the sample firms also improved in the post-merger years. However, the increment in firm performance was not because of the M&A itself, but a continuation from the pre-merger years. In other words, firms that combine through acquisition tend to maintain the same performance pattern as before, with little evidence of deviation either in a positive or negative direction. This suggests that post-merger synergies were not evident among the sample of acquisitions studied here. It also means that H₂ that the overall financial performance of the emerging country firms is likely to improve following acquisition of a firm from a developed country was not supported.

The individual analysis of each input and output variables used in the two stages of the DEA demonstrated that the values for brand equity, customer relationship expenditure, marketing expenditure and sales increased in the post-merger years compared to the pre-merger years and these changes were statistically significant. However, inventory turnover and EBIT declined in the post-merger years, although the decline in EBIT is not statistically significant. This may suggest, perhaps that large, well-resourced acquirer from emerging countries invest disproportionately in the development of the firms that they acquire which may be short of capital, resulting in a drag on profits in the short term. This is especially likely where the acquisition targets are distressed firms such as Jaguar/Land Rover and Volvo at the time that they were acquired by Tata and Geely, respectively.

Overall, our results partially supported our first hypothesis (H₁) that the marketing capability of emerging country firms will be improved following acquisition of a firm from a developed country is partially supported. This hypothesis rested on the argument that the marketing capability of emerging country firms is likely to be enhanced by acquiring established brands and the skills and resources of firms in developed markets. Our results indicate that this is certainly the case. The intuitive logic of firms from emerging markets wanting to purchase strong brands in developed markets as a means of accessing those markets on a large scale rather than trying to build new brands organically seems entirely compelling, and this research bears out the validity of such a strategy.

However, the price to be paid to get access to major global brands is often very high because of the need to invest heavily, particularly in capital intensive industries such as autos. Our second hypothesis (H₂) was that the overall financial performance of the emerging market firms is likely to improve in the post-merger years. Our findings from the DEA window analysis suggested that overall firm performance did improve following acquisitions. However, it turned out that this improvement was not so much because of the acquisitions as it was a continuation of the performance trajectory from the pre-merger years, in other words, it was a momentum effect. Our second hypothesis (H₂) was therefore not supported. This finding has interesting implications from a strategic point of view. It suggests that acquiring a strong firm with good, consistent financial performance is the best bet as this is likely to be maintained. In contrast, it offers little support for the possibility of acquiring a business with a view to trying to turn it around.

To the best of our knowledge, no other study has investigated the impact of acquisitions on the marketing capability of emerging market acquirers, so there is no previous evidence against which to benchmark this study. This study, therefore, fills a conspicuous gap in the literature. This study provides empirical evidence for the theoretical proposition that emerging market firms gain from acquisition of developed country firms through the integration of marketing assets and skills from the target firm.

Our findings on overall firm performance might be compared with studies by Boateng et al. (2008) who found that cross-border acquisitions by Chinese acquiring firms have a positive impact on shareholder wealth. Our results might also be comparable to a study of Indian acquiring firms by Gubbi et al. (2010) who found that cross-border acquisitions had a positive impact on combined shareholder wealth. Our results also support the findings of Bhagat et al. (2011) who demonstrated that the stock market rewards emerging market acquirers.

It should be noted, however, that all of these studies measured firm performance based on stock market reactions to acquisition announcements, while this current study used accounting data to track actual operating performance over a 4-year window (from 2 years before the acquisition to 2 years after) which is a tougher test. Our results suggest a more nuanced view which is that M&A by firms from emerging countries do yield growth in overall financial performance but not necessarily by a larger increment than both firms would have delivered without the merger. In other words, firms performing well on their own continue to perform well when combined, but do not necessarily enjoy any real synergistic effect (2 + 2 = 5) from combining. Conversely, it may be surmised that weak firms combining or a combination of weak and strong will not necessarily produce a significant change in the performance path of either, or both combined. That is a question for further research.

From a methodological standpoint, this study demonstrates that two-stage DEA can be used to disentangle individual effects, such as how particular capabilities affect overall performance of the firm. This longitudinal analysis is far superior to the more usual cross-sectional approach followed by marketing researchers. Undoubtedly, there is considerable further potential to make use of this methodology to increase our understanding of the dynamics of firm capabilities in marketing and in other areas.

The findings of this study have significant managerial implications. The results demonstrate that it is a valid and potentially rewarding strategy for emerging-market firms to consider acquiring firms based in developed countries as a way of gaining large-scale market access and building a strong presence for themselves. The results of this study provide empirical evidence that emerging market firms with inferior marketing capability can heighten their market management skill by leveraging the marketing assets and skills of the target firm. However, this enhancement in marketing capability may only assist the emerging-market firms to build their overall financial performance if they acquire firms with acceptable financial performance and growth momentum that can be expected to continue into the future. The alternative scenario – buying weak firms and trying to turn them around is a far more challenging scenario for which we have no supportive evidence.

Like all research, this study has some limitations. One of the fundamental assumptions of DEA is that all DMUs are homogeneous. As this study drew its sample from multiple industries, homogeneity of the DMUs could not be ascertained. Future studies should endeavour to establish the homogeneity of the sampled firms by taking into account variables such as firm size and the breadth and diversity of brand/product portfolios. While the sample size of this study was consistent with similar studies, future studies should be conducted with larger samples from a diverse range of industries. The context of emerging markets and cross-border M&A is one which merits particular attention, as it is a growing sector that has not yet received much research attention. Finally, future studies should examine under what conditions the marketing capability of the emerging market firms improves by incorporating various internal and external contextual variables.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Mahabubur Rahman

SM Riad Shams

Appendix

Table 3A.

Overall firm financial performance score for the pre- and post-merger years (DEA window analysis second stage. Window width 1).

DMUs (M&A Deals)	Pre-merger (t − 2) score	Pre-merger (t − 1) score	Post-merger (t + 1) score	Post-merger (t + 2) score
1	0.3318	0.1434	0.3093	0.373
2	0.148	0.058	0.1667	0.0655
3	0.0129	0.0156	0.0021	0.0035
4	0.0939	0.1091	0.1041	0.0631
5	0.2833	0.0844	0.0213	1
6	0.2149	0.2109	0.2916	0.2479
7	0.7995	0.4442	0.8455	0.4509
8	0.411	0.3549	1	0.9934
9	0.2429	0.2189	0.3099	0.0384
10	1	1	1	1
11	0.2801	0.6268	0.525	0.9926
12	1	1	1	1
13	1	1	1	1
14	0.1647	0.0568	0.1377	0.1302
15	0.6196	0.4211	0.2541	0.4048
16	0.0463	0.0317	0.1902	0.0984
17	0.1316	0.0692	0.0331	0.1398
18	0.1405	0.0672	1	0.1468
19	0.0269	0.0605	0.1897	0.1223
20	0.0205	0.0241	0.0832	0.2087
21	0.2609	0.128	1	1
22	0.3174	0.5003	0.4456	0.2924
23	0.1235	0.0354	0.0904	0.1408
24	0.1392	0.482	0.6064	0.7475
25	0.0986	0.0304	0.0513	0.0809
26	0.0106	0.0101	0.0161	0.01
27	0.3825	0.5251	0.3351	0.4661
28	0.1595	0.2123	0.3246	0.2384
29	0.0131	0.0091	0.0108	0.0107
30	0.0931	1	0.1392	0.1368
31	0.0653	1	1	1
32	0.0216	0.0071	0.0075	0.0188
33	0.0525	0.0287	0.1437	0.3408
34	0.0058	0.0013	0.0052	0.0072

DEA: data envelopment analysis; DMU: decision-making unit; M&A: merger and acquisition.

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