Strategy and cost stickiness under different managerial abilities: Evidence from Southeast Asia

Abstract

Firms’ strategies reflect their competitive advantages, such as the prospector focuses on innovation and defenders focus on cost efficiency. The differences in strategies’ competitive advantages imply different resource management to different magnitude of cost stickiness. This study examined whether prospectors and defenders exhibit different magnitude of cost stickiness. This study also examines cost stickiness differences in high and low managerial abilities for prospector and defender. The study investigates 24,362 firm-year observations in six Southeast Asian countries in 2013–2019. The results show that Southeast Asian firms exhibit cost stickiness. Both prospectors and defenders exhibit cost stickiness, likely because Southeast Asian firms mostly operate in raw goods trading and do not innovate much in high technology. Consequently, prospectors do not exhibit different cost behavior than defenders. Our findings document that firms led by less able managers exhibit greater cost stickiness, both for prospectors and defenders. The results suggest that managerial characteristics remain crucial in resource management, because less able managers tend to retain resources to cope with operational problems and meet future sales demands.

Keywords:

• cost stickiness
• strategy
• prospector
• defender
• managerial ability
• Southeast Asia

1. Introduction

Cost stickiness refers to an increase in costs due to an increase in the activity volume that is not followed by a symmetrical decrease in costs due to an activity decrease at the same level, as selling, general, and administrative (SG&A) expenses increase by 0.55% per 1% increase in sales but only decrease by 0.35% per 1% sales decrease (Anderson et al., 2003). Cost stickiness is usually associated with resource adjustment costs, i.e., costs to reduce resources when sales decline and reacquire the resources when activities return to their previous levels. When sales decline, eliminating idle resources with high adjustment costs may be more costly than keeping them. Hence, resources with high adjustment costs lead to greater cost stickiness (Anderson et al., 2003).

The basic premise of cost stickiness is that managers make contracts for their organizational resources, and terminating or renegotiating these contracts is costly (Calleja et al., 2006). When demands decline, managers may decide to keep idle resources instead of incurring the costs of terminating contracts. When firms report a sales decline, costs will not fall in the same proportion as the sales decline. When sales fluctuate, managers must determine whether and to what extent to adjust resource levels, considering associated adjustment costs. The interaction between managerial decisions and adjustment costs results in resource adjustment dynamics. Managers’ resource decisions depend not only on current sales but also on (1) prior resource levels that affect current adjustment costs, (2) expected future sales that affect future adjustment costs, and (3) agency and behavioral problems that drive the differences between optimal firms’ decisions and managers’ actual decisions (Banker & Byzalov, 2014).

Managers’ resource decisions are influenced by various factors, such as current resources, expected future sales, and firms’ operations (including strategy). Various strategies (such as prospectors vs. defenders) likely affect firms’ resource decisions. Prospectors focus on product research & development (R&D) and invest heavily in these activities. In the period of sales decline, firms tend not to reduce resources because resources are needed in the long term. Retaining resources leads to cost stickiness. Meanwhile, defenders focus on cost efficiency. In the period of sales decline, firms immediately reduce resources for cost efficiency. Reducing resources when sales decline leads to lower cost stickiness or cost anti-stickiness. Cost anti-stickiness exists when resource reduction in sales-increase periods is greater than the increase in resources in sales increase periods.

This study examines cost stickiness of prospector and defender strategies. Different strategies result in different resource allocation decisions. In real option framework, firms’ strategies have a different impact on investment, on how and when to invest. Firms’ strategies also arguably affect resource management that then leads to cost stickiness levels. Prospectors focus on innovation and heavily invest in intangible resources. Their managers tend to retain resources when sales decline because they need these resources to continue innovation. Meanwhile, defenders focus on cost efficiency and likely reduce costs when not needed to reduce adjustment costs due to retaining resources. Their managers tend to reduce resources when sales decline for cost efficiency purposes. Prior studies demonstrate that firms with a prospector strategy exhibit greater cost stickiness than those with a defender strategy (Banker, Flasher et al., 2014), and prospectors exhibit cost stickiness while defenders experience cost anti-stickiness (Ballas et al., 2022).

This study also examines cost stickiness under prospector and defender strategies in different managerial abilities. In upper echelon theory view, top managers’ characteristics can explain firms’ behavior because they make important decisions for their firms, and their personal characteristics significantly influence the decision-making processes, includes the managerial abilities. The previous cost stickiness literature largely examines the effect of operational variables on cost stickiness and has not considered that managers likely have different decision-making abilities. These studies assume that managers generally have similar abilities to manage resources and assess adjustment costs. However, different managerial abilities can affect resources decisions. Managerial ability is a manager’s superior ability to manage a firm compared to other firms in the same industry (Demerjian et al., 2012). Better able managers can maximize firms’ resources, evaluate technological trends, and explore market opportunities that enable them to increase future sales. They are also more optimistic about future sales. Optimistic sales expectations motivate managers to retain resources when sales decline, leading to higher cost stickiness. Managers who have a pessimistic view are more likely to predict declining future sales and consequently tend to reduce more resources, resulting in lower cost stickiness or cost anti-stickiness (Anderson et al., 2003; Banker & Byzalov, 2014; Banker, Byzalov et al., 2014).

This study analyzes non-financial firms from six Southeast Asian countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) in 2013–2019. Southeast Asia offers a unique setting because most firms are family-owned that tend to exhibit a higher cost stickiness behavior than non-family owned firms (Prabowo, 2019). Family firms tend to retain resources when sales decline to preserve their reputation (i.e. they tend not to lay off employees when sales decline). Southeast Asian firms also largely operate in the agricultural, mineral resources, and (recently) service sectors (Chong et al., 2020). They emphasize trading raw materials or low-tech products with their external partners (Hamid & Aslam, 2017). Consequently, these firms do not prioritize technology-related innovations that likely affect cost stickiness.

This study offers several contributions to cost stickiness research. First, our results empirically document cost stickiness in the Southeast Asian region. Further, in contrast to previous studies demonstrating that prospectors exhibit greater cost stickiness than defenders, this study document that both prospectors and defenders exhibit cost stickiness likely because most Southeast Asian firms operate in agricultural, mineral resources, and services industries that do not prioritize innovation. Similarly, prospectors and defenders in Southeast Asia exhibit similar cost stickiness behavior likely because of firms’ positions as subsidiary firms and the fact that innovation in subsidiary firms follows the innovation in the parent firms. Our research result provides additional evidence that cost stickiness behavior is not similar across countries, depending on the geographic area, the local culture and values adopted by the firms in a particular country.

Second, the findings empirically reveal that managerial ability, especially lower ones, affects cost stickiness. Both prospectors and defenders led by less able managers exhibit greater cost stickiness. The results indicate that managers’ characteristics remain crucial in their decision-making processes. In contrast to previous studies, that cost stickiness was higher in firms led by less able manager, the results of this study documented that cost stickiness was higher in firms led by less able manager. Our results empirically demonstrate that less able managers of Southeast Asian firms, which are mostly family-owned, are more likely to retain resources in the periods of declining sales that results in higher cost stickiness. Family-owned firms’ emphasis on their reputation motivates them to hire managers with lower abilities (Simamora, 2022)

The remainder of the paper is organized as follows. Section 2 reviews the literature. Section 3 develops hypotheses. Section 4 discusses the sampling technique and research method. Section 5 presents the findings and robustness checks, and section 6 concludes.

2. Literature review

This section reviews prior literature on firms’ strategy, managerial ability, and cost stickiness.

2.1. Firm’s strategy

Prospector strategy focuses on innovation and market opportunities (Jabnoun et al., 2003). Firms adopting this strategy tend to prioritize creativity and flexibility over efficiency to respond to market conditions and explore new market opportunities. Prospectors also seek and exploit new product and market opportunities. This strategy has a wide and expanding market, transforms the industry, and grows through product and market development. This strategy’s technology is flexible and prototypical, and it frequently employs many technologies. This strategy emphasizes marketing and product research and development through innovations (Miles et al., 1978).

The defender strategy focuses on cost efficiency. It also emphasizes production and distribution efficiency. This strategy seeks market stability and offers products that are limited to small and potential market segments (Jabnoun et al., 2003). Defenders have narrow but stable markets, and strongly maintain their markets by offering competitive prices or better customer services. They only rely on a single cost-efficient technology (Miles et al., 1978). Defenders compete on price, quality, delivery, and service. They also focus on operational efficiency and strict cost control to maintain competitive positions.

2.2. Managerial ability

Managerial ability is broadly defined as managers’ knowledge and experience of their firms and business environments that enable managers to utilize resources more efficiently (Demerjian et al., 2012). Managerial ability refers to a manager’s knowledge, skills and experience. Managers develop their managerial abilities, including the ability to analyze the markets and determine appropriate strategies and technology, from their managerial experience (Kor, 2003). Better able managers tend to have broader business knowledge, greater ability to assess the current situation and forecast product demands, better familiarity with technology and industry trends, and greater efficiency in managing employees (Demerjian et al., 2013, 2012). They arguably can better align resources with their operating environments, resulting in higher internal profitability.

2.3. Cost stickiness

Cost stickiness describes as increase in costs due to an increase in the activity volume that is not followed by a symmetrical decrease in costs due to an activity decrease at the same level (Anderson et al., 2003). Costs are sticky if the magnitude of the increase in costs associated with the increase in volume is greater than the magnitude of the decrease in costs associated with an equivalent decrease in volume.

The cost stickiness research assumes resource asymmetry in predicting sales and costs changes. There are three major determinants of cost stickiness: (1) resource adjustment cost; (2) future sales expectation; and (3) managerial incentives and their interactions with governance, regulation, and ownership.

Prior literature on cost stickiness determinant largely classifies the determinants based on cost stickiness drivers. The first group is such as employee and asset intensity (Anderson et al., 2003; Banker & Byzalov, 2014), inventory intensity (Subramaniam & Watson, 2016), adjustment costs in core activities (Balakrishnan & Gruca, 2008), labor adjustment costs (Banker et al., 2013), strategy (Banker, Flasher et al., 2014), and intangible assets (Mohammadi & Taherkhani, 2017; Venieris et al., 2015). The second group including GDP growth as a proxy for managerial optimism (Anderson et al., 2003; Banker & Byzalov, 2014; Banker, Byzalov et al., 2014), successive decrease (Banker & Byzalov, 2014; Subramaniam & Watson, 2016), and successive increase (Banker, Byzalov et al., 2014). The third group including general elections (Lee et al., 2019), empire-building incentives (Chen et al., 2012), performance compensation (Brüggen & Zehnder, 2014), performance benchmarks (Banker & Byzalov, 2014; Dierynck et al., 2012; Kama & Weiss, 2013), regulations (Holzhacker et al., 2015), ownership (Holzhacker et al., 2015; Prabowo et al., 2018), firms’ characteristics (Liu et al., 2019), corporate social responsibility (Habib & Hasan, 2016), and competition (Cheung et al., 2018; Li & Zheng, 2017). In addition, managers’ behaviors, such as overconfidence (Chen et al., 2018; Qin et al., 2015), and their personal characteristics (Liang et al., 2015; Yang, 2015), also determine cost stickiness.

3. Hypothesis development

3.1. Strategy and cost stickiness

The relationship between strategy and cost stickiness can be explained using the real options theory. Firms’ strategic orientation affects their investment decisions. Firms make investment decisions based on the competitive advantages of each strategy. On the one hand, prospectors are more innovative and engaged in organizational activities that require resources to develop specific resource strategies, such as R&D, advertising, human resource development, and advanced relationship management systems (Ballas et al., 2022). Firms with a prospector strategy focus on innovation and do not delay investments to exploit market opportunities. They also tend to invest in long-term marketing and R&D activities and intangible assets, including human resources or organizational capital, as the sources of core capabilities and sustainable competitive advantage. Their assets are usually firm-specific because they are acquired and developed based on firms’ needs. These assets cannot be used outside the firms and have no economic value for other firms. For example, firms cannot sell their specific resources such as scientists or R&D staff, workers with specialized production skills, skilled sales and marketing staff, managers who understand the organization’s culture, routines and processes, and specialized production facilities (Banker, Flasher et al., 2014). Human resources and organizational capital are non-tradable and have lower market values but are valuable to the firms. Reducing these resources when sales decline and reacquiring them when sales increase is costly. Thus, when sales decline temporarily, these firms tend to retain resources until the subsequent period, given that the adjustment costs exceed the benefits of reducing resources (cost savings).

Specialized resources are not easily marketable because they are developed over a long period and cannot be directly purchased from the markets. In addition, firms should invest in employee training to acquire skilled workforces and salespersons. It takes a long period for new R&D employees and managers to learn tacit knowledge within their firms. Prospectors incur higher adjustment costs of resource capacities. Prospectors that reduce resources when sales decline will incur higher adjustment costs when sales increase again. Thus, prospectors tend to retain resources although current sales decline.

On the other hand, defenders emphasize the efficiency of production and distribution of goods and services. They also focus on achieving incremental growth through market penetration, efficient cost management, and efficiency-enhancing technologies. They focus on cost control activities, such as short product development cycles, standardized product designs, procurement of low-cost raw materials and labor, full utilization of capacity resources, low-cost distribution channels, tight budget control on overhead costs, research and development costs, and marketing and sales costs, to achieve their goals (Banker, Flasher et al., 2014). In addition, defenders’ targeted consumers are usually price-sensitive and pay less attention to non-price dimensions than prospectors’ consumers. Consequently, defenders must maintain substantial operating scale and market share instead of acquiring dedicated resources because their long-term success hinges on low-margin business models and high resource turnovers. When current sales decline, defenders have to cut product prices to maintain or increase market shares. Defenders can also reduce idle capacities easily to reduce losses. They also easily reacquire resources when sales rebound because their resources are less specialized or unique than prospectors.

This study predicts that prospectors exhibit higher cost stickiness than defenders because of differences in operating emphasis. Prospectors focus on innovation and exploit market opportunities. They tend to invest in long-term R&D activities and intangible assets. When sales decline, they tend to retain resources to continue R&D and innovation activities, resulting in higher cost stickiness. Meanwhile, defenders focus on efficiency. They tend to reduce resource when sales decline to achieve cost efficiency, leading to lower cost stickiness. Previous studies also demonstrate that prospectors exhibit higher cost stickiness than defenders (Banker, Flasher et al., 2014), and prospectors exhibit cost stickiness, while defenders cost anti-stickiness (Ballas et al., 2022).

H1. Prospectors exhibit greater cost stickiness than defenders.

3.2. Cost stickiness in different strategies and managerial abilities

The upper echelon theory explains the relationship between managerial ability and cost stickiness. This theory argues that executives’ experience, values, and personalities greatly influence how they interpret situations and make decisions (Hambrick, 2007). One of managers’ individual characteristics is their abilities. Better able managers arguably understand industry and technology trends better, predict sales more accurately, invest in projects with higher net present value, and manage resources more efficiently than less able managers (Demerjian et al., 2012). Further, better able managers manage resources based on their firms’ strategies and competitive advantages. Managerial ability determines the efficiency of business strategy implementation and is a crucial intangible asset. In other words, the efficiency of strategic plan implementation is affected by the efficiency of firms’ management capabilities. Different managerial ability levels likely cause firms with similar strategic orientations to exhibit different strategic choice implementations (Ballas et al., 2022).

This study predicts that managerial ability affects prospectors’ and defenders’ cost stickiness. Better able managers manage resources more efficiently, predict sales more accurately, and have a more optimistic outlook for future sales. Additionally, they can also exploit market opportunities and manage resources to maximize future profits.

On one hand, prospectors focus on innovation to develop new products and markets. These firms use their resources for innovations that often require specialized resources (such as skilled labor and organizational capital). Due to the scarcity of these specialized resources on the market and the length of time required to develop them, managers frequently retain them when current sales decline. Firms that release resources when sales decline will find it more difficult to reacquire these resources when sales rise again. In this respect, retaining resources leads to higher cost stickiness. Better able managers consider optimistic signals when making resource adjustments. Greater optimism motivates managers to retain resources when current sales decline to anticipate future sales increases.

Prospectors led by better able managers exhibit greater cost stickiness than those led by less able managers. When sales fall, better able managers in prospectors tend to retain resources for innovation and new market opportunity exploration. R&D should continue despite a temporary sales decline and reducing resources delays innovation. These managers are also more optimistic of sales prospects and consequently tend to retain resources to fulfill future sales, resulting in higher cost stickiness.

H2a. Prospectors led by better able managers exhibit greater cost stickiness than prospectors led by less able managers.

On the other hand, defenders emphasize cost efficiency. Better able managers manage resources that emphasize cost efficiency. They tend to reduce resources when sales decline because they are unwilling to incur adjustment costs from retaining resources. Managers also tend to reduce resources because not firm-specific resource and easily available in the market. These resources are easily replaced to anticipate increased sales. In addition, defenders’ managers make future sales expectations more conservatively than prospectors’ (Ballas et al., 2022). Thus, they are less likely to retain resources when anticipating future sales increases. Meanwhile, less able managers tend to retain resources to meet resource needs and anticipate future sales increases because of their inability to manage resources efficiently. Retaining resources when sales decline increases cost stickiness.

Defenders led by less able managers likely exhibit greater cost stickiness than those led by better able managers. Less able managers have limited ability to utilize the necessary capacity for firm’s operations. Unutilized operating capacity results in idle resources, which, if not reduced when sales decline, lead to cost stickiness. Higher predicted future sales also motivate managers to maintain resources to meet future sales, leading to higher cost stickiness.

H2b. Defenders led by less able managers exhibit greater cost stickiness than defenders led by better able managers.

4. Methods

We use listed non-financial firms from 6 (six) Southeast Asian countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam) in 2013–2019 as our data. Financial data was obtained from the Thompson Reuters database. Brunei Darussalam and Timor Leste are excluded because they have no stock exchange. We also exclude Cambodia, Lao PDR, and Myanmar due to lack of data (data is not available in the Thompson Reuters database). Total observation listed non-financial firms in 2013–2019 is 33,152 firm-years. Following Anderson et al. (2003) and Banker et al. (2013), we eliminate missing, zero, or negative data for SG&A costs for t and t-2 (7,579 firm-years observation). We also delete observations with SGA_t > Sales_t or SGA_t-1 > Sales _t-1 (1,211 firm-years observation). The final sample is 24,362 firm-years observations.

Following Anderson et al. (2003) and Chen et al. (2012), we employ the following model to test the hypotheses:

$\begin{array}{rl}& \mathrm{\Delta }\mathit{\text{LnSG}}{A}_{i,t}={\beta }_0+{\beta }_1\mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}+{\beta }_2 \mathit{\text{De}}{c}_{i,t}\ast \mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}+{\beta }_3 \mathit{\text{AsIn}}{t}_{i,t}\ast \mathit{\text{De}}{c}_{i,t}\ast \mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}\\ & +{\beta }_4 \mathit{\text{SucDe}}{c}_{i,t}\ast \mathit{\text{De}}{c}_{i,t}\ast \mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}+{\beta }_5 \mathit{\text{Growt}}{h}_{i,t}\ast \mathit{\text{De}}{c}_{i,t}\ast \mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}\\ & +{\beta }_6 \mathit{\text{AsIn}}{t}_{i,t}+{\beta }_7 \mathit{\text{SucDe}}{c}_{i,t}+{\beta }_8 \mathit{\text{Growt}}{h}_{i,t}+{\epsilon }_{i,t}\end{array}$

ΔLnSGA is natural logarithm changes in SG&A cost, ΔLnSales is natural logarithm changes in sales. SGA and Sales are deflated Selling, General & Administrative costs, and net sales, respectively (we deflate Selling, General & Administrative costs and net sales with the consumer price index) The i and t subscripts refer to firm i and year t, respectively. Dec is a dummy variable that equals 1 if sales decrease in the current year and 0 otherwise. We use fixed effect for the panel estimation. Fixed effect model assumes that differences between individual observations can be accommodated from different intercept. The intercept of the regression model is allowed to vary independently between individuals or groups.

This study measures cost stickiness based on Anderson et al. (2003) who use a linear relationship between the log of changes in SGA costs and the log of changes in sales and sales declines. Anderson et al. (2003) use the log-log specification in linear equations because the log form of change increases the comparability of variables between firms and reduces heteroscedasticity. The formula is as follows:

$ln\left[\frac{\mathit{\text{Cos}}{t}_{i,t}}{\mathit{\text{Cos}}{t}_{i,t-1}}\right]={\beta }_0+{\beta }_{1}ln\left[\frac{\mathit{\text{Sale}}{s}_{i,t}}{\mathit{\text{Sale}}{s}_{i,t-1}}\right]+{\beta }_2\ast \mathit{\text{De}}{c}_{i,t}\ast \ln \left[\frac{\mathit{\text{Sale}}{s}_{i,t}}{\mathit{\text{Sale}}{s}_{i,t-1}}\right]+{\epsilon }_{i,t}$

Dec is a dummy variable that equals 1 if sales decrease in the current year and 0 otherwise. The cost is sticky if β₁ > 0 and β₂ < 0.

This study uses selling, general, and administrative (SG&A) costs because these costs constitute a significant proportion of firms’ operating costs. SG&A costs also represent a large part of firms’ indirect costs (Chen et al., 2012). In particular, these costs are related to the procurement and development of organizational capital, such as information systems, employee training, research and development, consulting, and promotion costs (Lev et al., 2009).

This study identifies prospector and defender strategies (STRA) in the analysis. We categorize firms as prospectors and defenders by following Gani & Jermias (2006) who develop the classification based on three ratios, namely R&D intensity, asset utilization efficiency, and premium price capability. Because most Southeast Asian firms do not widely disclose the R&D data, R&D intensity is not used. We add the ratio of sales/capital expenditure to measure efficiency. Asset utilization efficiency (AUE) is calculated by dividing total sales by total assets. Premium price capability (PPC) is operationalized by dividing gross margin by total sales. Lastly, Sales/Capex (SCAP) is calculated by dividing total sales by capital expenditure. After obtaining the AUE, PPC, and SCAP values, we then divide the observations into the high or low groups based on the median values in each industry and year. Firms are considered prospectors (defenders) if their PPCs are above (below) the median values and AUEs & SCAPs are below (above) the median values.

This study measures managerial ability (MA) by referring to Demerjian et al. (2012) who measure managers’ abilities based on their efficiency in utilizing firms’ resources. Specifically, they operationalize managerial ability as a manager’s efficiency in converting available resources into income relative to other firms in the same industry. The managerial ability measure employs Data Envelopment Analysis (DEA) to estimate industrial efficiency by comparing each firm’s sales (output) with seven criteria (inputs), namely cost of goods sold, SG&A expenses, net fixed assets, net operating leases, net (R&D) expenses, purchases of goodwill, and other intangible assets. Next, the efficiency value is regressed with firm-specific characteristics (firm size, market share, positive free cash flow value, firm age, business segment, and country currency rate indicator) using the Tobit analysis. The regression’s residual value represents managerial ability.

The control variables used in this study are asset intensity, successive decrease, and GDP growth. Asset intensity (AsInt) is measured by dividing total assets by net sales. Meanwhile, the successive decrease (SucDec) variable is measured by a dummy variable that equals one if sales_it < sales_it-1 < sales_it-2 and zero otherwise. Lastly, GDP growth (Growth) is obtained from the World Bank’s GDP growth data (annual %).

5. Empirical results

5.1. Descriptive statistics

Our main interest is cost stickiness as the regression between ΔLnSGA and ΔLnSales and the interaction of Dec with ΔLnSales. Descriptive statistics can be seen in Table 1. The overall mean value of ΔLnSGA is 0.042, implying that the log value of changes in SG&A costs of the overall average observation is 4.2%. The overall mean value of ΔLnSales is 0.025, indicating that the log value of sales changes of the overall average observation is 2.5%. Meanwhile, the Dec variable represents a decrease in sales with a mean value of 0.445. Hence, 44.5% of observations experience a decrease in sales. Overall, there are 12,017 prospectors and 12,345 defenders. The proportions of prospectors and defenders are relatively balanced (49.3% and 50.7% for prospectors and defenders, respectively). Lastly, we have 12,699 observations with high managerial abilities and 11,663 observations with low managerial abilities (52.1% and 47.9% of total observations, respectively). The pairwise correlations between variables can be seen in Table 2. Almost all variables are significantly correlated with other variables.

Table 1. Descriptive statistics

	Mean
Variable	Overall	Indonesia	Malaysia	Philippines	Singapore	Thailand	Vietnam
ΔLnSGA	0.042	0.073	0.021	0.074	0.024	0.071	0.03
ΔLnSales	0.025	0.044	0.001	0.073	0.001	0.046	0.026
Dec	0.445	0.423	0.479	0.356	0.472	0.42	0.443
STRA	0.493	0.492	0.497	0.466	0.464	0.495	0.51
MA	0.521	0.496	0.505	0.504	0.5	0.511	0.568
AsInt	3.045	3.32	3.251	5.609	3.748	2.244	2.439
SucDec	0.211	0.19	0.234	0.161	0.232	0.194	0.211
Growth	0.049	0.051	0.05	0.066	0.033	0.03	0.065
Obs	24,362	3220	5363	1149	3633	4275	6722

5.2. Results

Table 3, column 1 shows the overall cost stickiness. The test results suggest that the coefficient for ΔLnSales (β₁) (0.531, t = 14.20) is significant and positive at 1% while the coefficient for Dec*ΔLnSales (β₂) (−0.23, t = −3.72) is significant and negative at 1%. The results imply that our overall observations exhibit cost stickiness. On average, SG&A costs increase by 0.531% for every 1% increase in net sales, but only decrease by 0.301% (0.531%—0.23%) for every 1% decrease in net sales.

Table 2. Pairwise correlation

Variables	ΔLnSGA	ΔLnSales	Dec	STRA	MA	AsInt	SucDec	Growth
ΔLnSGA	1.000
ΔLnSales	0.469***	1.000
Dec	−0.248***	−0.555***	1.000
STRA	−0.012*	−0.073***	0.056***	1.000
MA	0.011*	0.091***	−0.087***	−0.181***	1.000
AsInt	−0.032***	−0.166***	0.088***	0.257***	−0.115***	1.000
SucDec	−0.160***	−0.325***	0.576***	0.055***	−0.090***	0.075***	1.000
Growth	0.000	0.017***	−0.031***	0.019***	0.034***	0.003	−0.020***	1.000

*** significance at the 1%; ** significance at the 5%; * significance at the 10%

Table 3. Hypothesis 1 test results

Dependent variable: ΔLnSGA
	(1)	(2) Pros	(3)Def
Variables	Coef. (t)	Coef. (t)	Coef. (t)
ΔLnSales (β1)	0.531***	0.544***	0.565***
	(14.02)	(11.79)	(8.27)
Dec*ΔLnSales (β2)	−0.23***	−0.213***	−0.358***
	(−3.72)	(−3.07)	(−3.22)
AsInt*Dec*ΔLnSales (β3)	0.003**	0.003*	0.03
	(2.02)	(1.74)	(0.40)
SucDec*Dec*ΔLnSales (β4)	−0.014	−0.05	0.173*
	(−0.27)	(−0.79)	(1.88)
Growth*Dec*ΔLnSales (β5)	−4.162**	−5.673***	−5.846
	(−2.03)	(−2.82)	(−1.50)
AsInt	0.008***	0.007**	0.006
	(3.60)	(2.57)	(0.68)
SucDec	−0.007	−0.009	0.023
	(−0.53)	(−0.50)	(1.24)
Growth	0.195	0.137	−0.397
	(0.52)	(0.22)	(−0.82)
Constant	−0.045***	−0.045***	−0.046**
	(−4.34)	(−2.93)	(−2.15)
Chow test		1.89
N	24362	12017	12345
R-sq	0.188	0.185	0.206
Fixed effect	yes	yes	yes
Hettest	robust	robust	robust

*** significance at the 1%; ** significance at the 5%; * significance at the 10%

The test results for hypothesis 1 can be seen in Table 3 columns (2) and (3). In the prospector sub-sample (Table 3 column (2)), the coefficient for ΔLnSales (β₁) (0.544, t = 11.79) is significant and positive at 1%, and the coefficient for Dec*ΔLnSales (β₂) (−0.213, t = −3.07) is significant and negative at 1%. Thus, prospectors exhibit cost stickiness. On average, SG&A costs increase by 0.544% for every 1% increase in net sales, but only decrease by 0.331% (0.544%—0.213%) for every 1% decrease in net sales. Meanwhile, in the defender sub-sample, the results document that the coefficient for ΔLnSales (β₁) (0.565, t = 8.27) is significant and positive at 1% and the coefficient for Dec*ΔLnSales (β₂) (−0.358, t = −3.22) is significant and negative at 1%, implying defenders also exhibit cost stickiness. On average, SG&A costs increase by 0.565% for every 1% increase in net sales, but only decrease by 0.207% (0.565%—0.358%) for every 1% decrease in net sales. The results of the chow test (F = 1.89, t = 0.1509) suggests that both subsamples do not exhibit significantly different degree of cost stickiness. Thus, hypothesis 1 predicting that prospectors exhibit higher cost stickiness is not supported because both prospectors and defenders have similar degrees of cost stickiness.

According to the real options framework, both prospectors and defenders exhibit cost stickiness because they choose investments according to their strategies and competitive advantages. Prospectors continue to invest in resources used to innovate and maintain competitive market positions while defenders invest lower resources when sales decline and use those resources to operate efficiently.

The test results reveal that prospectors exhibit cost stickiness. Prospectors are innovative, and their organizational activities require resources to develop specific resource strategies, such as R&D, marketing, and human resource development (Ballas et al., 2022). Firms with a prospector strategy continue investing by retaining resources for R&D and innovation.

The results also show that defenders exhibit cost stickiness even though defenders seek to achieve operational benefits through efficiencies resulting from lean cost structures and low customization costs. They also focus on cost efficiency by prioritizing cost-control activities, such as shorter new product development cycles, standard product designs, cheap raw materials and labor procurement, full utilization of resource capacity, and cost-effective distribution channels, low budgets, and tight budget control on overhead, R&D, and marketing costs (Banker, Flasher et al., 2014). When sales decline, defenders can quickly reduce idle capacities to reduce losses, cut product prices and eventually maintain or increase market shares. Defenders also easily reacquire resources when sales rise again because they need less specialized or unique resources than prospectors. Their focus on cost efficiency requires defenders to compare costs of retaining resources and adjustment costs. When sales decline, defenders hold resources optimally and reduce the remaining ones, leading to lower cost stickiness. Our results do not support previous studies that observe that prospectors exhibit greater cost stickiness than defenders (Ballas et al., 2022; Banker, Flasher et al., 2014).

Defenders and prospectors exhibit similar degrees of cost stickiness, likely because prospectors in these countries do not innovate much in high-technology or sophisticated innovation. Most ASEAN firms operate in the agricultural and mineral resource sectors and have started operating in the service sector (Chong et al., 2020). These firms put more emphasis on trading products or raw materials. They also rely heavily on trading less specifically produced goods (Hamid & Aslam, 2017). Consequently, prospectors in Southeast Asia do not need specific tools or expertise that must be maintained when sales decline. Firms retain sufficient resources to facilitate innovation. Another likely explanation is that many Southeast Asian firms are subsidiaries while R&D activities are carried out in their parent firms outside Southeast Asia. Subsidiary firms do not develop products locally but imitate parent firms’ R&D activities.

Table 4 shows the test results for hypothesis 2. For the prospectors with high managerial ability sub-sample, the coefficient for ΔLnSales (β₁) (0.516, t = 7.47) is significant and positive at 1%, and the variable Dec*ΔLnSales (β₂) (−0.114, t = −1.01) is not significant. Meanwhile, in the low managerial ability sub-sample, the coefficient for ΔLnSales (β₁) (0.587, t = 9.03) is significant and positive at 1% and the coefficient for Dec*ΔLnSales (β₂) (−0.309, t = −3.27) is significant and negative at 1%. Thus, only prospectors led by less able managers exhibit cost stickiness. The results of the Chow test (F = 8.33, t = 0.0002) suggest a significant regression coefficient difference between the high and low managerial ability sub-samples. In sum, hypothesis 2a is not empirically supported because in the prospector sub sample, we document cost stickiness in the low managerial ability group.

Table 4. Hypothesis 2 test results

	Dependent variabel: ΔLnSGA
	Prospector		Defender
	High MA	Low MA	High MA	Low MA
ΔLnSales (β1)	0.516***	0.587***	0.475***	0.745***
	(7.47)	(9.03)	(7.27)	(4.58)
Dec*ΔLnSales (β2)	−0.114	−0.309***	−0.21*	−0.669***
	(−1.01)	(−3.27)	(−1.94)	(−2.77)
AsInt*Dec*ΔLnSales (β3)	−0.003	0.004*	−0.014	0.005
	(−0.76)	(1.94)	(−1.06)	(0.49)
SucDec*Dec*ΔLnSales (β4)	−0.137	0.021	0.246**	0.282**
	(−1.01)	(0.26)	(2.30)	(2.33)
Growth*Dec*ΔLnSales (β5)	−1.655	−7.679**	3.859	−14.381***
	(−0.41)	(−3.30)	(1.28)	(−3.21)
AsInt	0.005	0.005*	0.001	0.005
	(1.03)	(1.70)	(0.09)	(0.32)
SucDec	−0.001	0.0002	0.028	0.044
	(−0.02)	(0.01)	(1.38)	(1.61)
Growth	1.311	−1.375*	0.31	−0.829
	(1.07)	(−1.89)	(0.55)	(−1.06)
Constant	−0.05	−0.038*	−0.029*	−0.068
	(−1.95)	(−1.87)	(−1.79)	(−1.36)
Chow test	8.33***		4.02**
N	5162	6855	7537	4808
R-sq	0.147	0.241	0.158	0.300
Fixed effect	yes	yes	yes	yes
Hettest	robust	robust	robust	robust

*** significance at the 1%; ** significance at the 5%; * significance at the 10%

For defenders with high managerial ability sub-sample, the test results show that the coefficient for ΔLnSales (β₁) (0.475, t = 7.27) is significantly positive at 1% and the coefficient for Dec*ΔLnSales (β₂) (−0.21, t = −1.94) is significantly negative at 10%. The findings imply that defenders led by better able managers exhibit cost stickiness. In the low managerial ability sub-sample, the test results reveal that the coefficient for ΔLnSales (β₁) (0.745, t = 4.58) is significantly positive at 1% and the coefficient for Dec*ΔLnSales (β₂) (−0.669, t = −2.77) is significantly negative at 1%. The results suggest that defenders led by less able managers exhibit cost stickiness. The results of the Chow test (F = 4.02, t = 0.0181) indicate a significant regression coefficient difference between the high and low managerial ability sub-sample. The low managerial ability sub-sample demonstrates higher statistical significance than the high managerial ability sub-sample. Consequently, hypothesis 2b that predicts that defenders led by less able managers exhibit greater cost stickiness than those led by better able managers is empirically supported.

The upper echelon theoretical framework suggests that managers’ characteristics affect decision-making processes, including resource-related ones. In this respect, this study observes that low managerial ability, as an example of managerial characteristics, causes higher cost stickiness. Managers with higher managerial abilities can manage their resources efficiently and overcome resource shortages due to sales growth. Hence, retaining resources is not their goal (Banker et al., 2021). Meanwhile, less able managers manage resources less efficiently and tend to retain resources instead of making costly resource adjustments.

5.3. Robustness test

Our robustness test measures cost stickiness using firm-year measurements (He et al., 2020). We then refer to Anderson’s model in determining sticky value using 16 quarters data and define Sticky as a negative value of β₂. Thus, higher Sticky values represent higher cost stickiness. The following is Anderson et al. (2003) equation:

$\mathrm{\Delta }\mathit{\text{LnSG}}{A}_{i,t}={\beta }_0+{\beta }_1\mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}+{\beta }_2\mathit{\text{De}}{c}_{i,t}\ast \mathrm{\Delta }\mathit{\text{LnSale}}{s}_{i,t}+\mu$

Following He et al. (2020) we employ the following model for the robustness test of H1:

$\mathit{\text{Stick}}{y}_{i,t}={\alpha }_0+{\alpha }_1\mathit{\text{STR}}{A}_{i,t}+{\alpha }_2\mathit{\text{AsIn}}{t}_{i,t}+{\alpha }_3\mathit{\text{SucDe}}{c}_{i,t}+{\alpha }_4\mathit{\text{Growt}}{h}_{i,t}+{\epsilon }_{i,t}$

For H2, this study runs the regressions on the prospector and defender sub-samples. Sticky is cost stickiness (He et al., 2020); STRA is a dummy variable that equals 1 if observation is a prospector and 0 otherwise; AsInt is asset intensity (Anderson et al., 2003); the successive decrease (SucDec) variable is measured by a dummy variable that equals one if sales_it < sales_it-1 < sales_it-2 and zero otherwise. Lastly, Growth refers to GDP growth.

Table 5 presents the results of the robustness test. Table 5 column (1) shows insignificant results, implying that prospectors do not exhibit greater cost stickiness than defenders. Our findings support the main test of H1. Defenders and prospectors exhibit similar cost behavior likely because prospectors in Southeast Asia do not innovate in high-technology, leading to lower cost stickiness. Meanwhile defenders must consider the costs of retaining resources and adjustment costs for efficiency reasons. These firms tend to retain resources when sales decline if retaining resources are more efficient, thus implying greater cost stickiness.

Table 5. Robustness tests

Dependent variable: Sticky
	(1)	(2) Pros	(3) Def
STRA	0.08
	(1.64)
MA		−0.032	−0.069
		(−0.52)	(−0.99)
AsInt	0.0000002***	0.000001***	−0.001***
	(4.11)	(3.67)	(−33.2)
SucDec	0.023	0.051	−0.029
	(0.54)	(0.83)	(−0.45)
Growth	−0.509	−0.888	−0.201
	(−0.26)	(−0.31)	(−0.07)
Constant	−0.081	0.014	−0.033
	(−0.83)	(0.10)	(−0.24)
Rsquare	0.0003	0.0003	0.001
N	16503	8244	8247

*** significance at the 1%; ** significance at the 5%; * significance at the 10%

Table 5 column (2) also reveals insignificant results, suggesting that prospectors led by better able managers do not exhibit greater cost stickiness than those led by less able managers. Similarly, for defenders, Table 5 column (3) indicates that firms led by better able managers do not exhibit greater cost stickiness than those led by less able managers. The results of our robustness tests document that prospectors and defenders led by better able managers exhibit similar cost behavior with those led by less able manager. Better able managers manage their resources efficiently and do not focus on retaining resources. Meanwhile, less able managers tend to retain resources when sales decline to avoid costly resource adjustments.

6. Conclusions

This study examines the cost stickiness of firms adopting the prospector and defender strategies because firms’ strategies arguably determine their resource decisions. This study also analyzes prospectors’ and defenders’ cost stickiness under different managerial abilities. We conduct this study in 6 (six) Southeast Asian countries in 2013–2019. The results demonstrate the presence of cost stickiness, and prospectors and defenders do not exhibit significantly different magnitude of cost stickiness. A likely explanation of our findings is that prospectors in Southeast Asia tend to be less innovative in high technology and operate on raw natural products. Consequently, these firms do not retain their resources for innovation. Meanwhile, defenders retain resources because they consider the costs of retaining resources lower than adjustment costs. The results also show that less able manager is associated with greater cost stickiness, both for prospectors and defenders. Less able managers manage resources less efficiently and tend to retain resources to operate and meet future sales expectations. Meanwhile, better able managers manage resources efficiently and mitigate problems related to resource shortages that retaining resources is not their goal.

Our study implies that investors need to identify countries’ characteristics in their investment decisions because both prospectors and defenders in Southeast Asian countries exhibit cost stickiness. Investors also need to evaluate firms’ managerial capabilities that likely affect cost stickiness. Further, managers with similar country characteristics make similar resource decisions. Firms tend to retain resources when sales decline. Managers’ lower abilities also explain firms’ decisions to retain resources that lead to higher cost stickiness.

Our results offer firm-level policy implication. Retaining resources when sales decline lead to higher cost stickiness that provide either a positive or negative signal to outsiders. Specifically, firms retain resources to meet increased future sales (a positive signal), albeit incurring lower current profits (a negative signal). Further, firms must improve their managerial ability to enable their managers manage resource efficiently and retain sufficient resources, and eventually firms can maintain lower cost stickiness.

This study is limited to six Southeast Asian countries (Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) because we lack data for other countries. Further studies can explore all Asian countries and investigate cost stickiness in each country. Further, we advise future studies to explore the country-level determinants of cost stickiness in Asian countries like different cultural values and institutions.

Disclosure statement

The authors have no potential conflicts of interest to declare.

Additional information

Funding

The authors received no direct funding for this research.

Notes on contributors

Mitha Dwi Restuti

Mitha Dwi Restuti is Doctoral Student in the Accounting Postgraduate Program, Universitas Indonesia. She is a lecturer at Department of Accounting Universitas Kristen Satya Wacana. Her research interests focus on Managerial Accounting and Cost Accounting.

Lindawati Gani

Lindawati Gani is a Professor in Management Accounting at the Department of Accounting, Universitas Indonesia. She obtained her Doctoral degree from Universitas Indonesia. Her research interests focus on Management Accounting, Governance, and Integrated Reporting.

Elvia R. Shauki

Elvia R. Shauki is a Senior Lecturer in the Department of Accounting, Universitas Indonesia. She obtained her Doctoral degree from La Trobe University Australia. Her research interest focus on financial accounting, financial reporting and sustainability reporting.

Lianny Leo

Lianny Leo is a lecturer in the Department of Accounting, Universitas Indonesia. She obtained her Doctoral degree from Universitas Indonesia. Her research interests focus on financial and management accounting.