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The purpose of this paper is to identify the sources of variation in firm performance. This is one of the cornerstones of strategy research, i.e. the relative importance of industry and firm-level effects on firm performance. Multilevel analysis is well suited to analyze variance in performance when the data are hierarchically structured (industry segments consist of firms, firms operate within the context of industry segments). The Belgian industry studied is a service industry that consists of about 25 electrical wholesalers. Data were collected from 20 firms during the period 1998–2003 from responses to a questionnaire sent to all the firms in the market. The sample in the data set covers more than 95 percent of the market (in sales), as the missing firms were just fringe competitors. The results show that firm effects explain most of the variance in four performance variables. That bears out the importance of each firm having its own specific, idiosyncratic resources and competences. The explanatory power of firm effects varies by about 30–40 percent while the intra-industry effect explains around 10 percent of the variance. Even though firm effects are dominant, intra-industry effects explain a significant portion of the variance in firm-level performance. The firm effect is smaller than in previous studies. The firm effect varies across the performance measures: firm effects are higher for returns on assets than for profit margins. The industry segment effect (or intra-industry effect) is more independent of the dependent variable. The industry segment effect is in line with previous studies on the strategic group effect. Top managers should carefully choose and monitor the intra-industry domain they are in.

This paper uses two complementary approaches to estimate the effect of right-to-work (RTW) laws on wages and unionization rates. The first approach uses an event study design to analyze the impact of the adoption of RTW laws in five US states since 2011. The second approach relies on a differential exposure design that exploits the differential impact of RTW laws on industries with high unionization rates relative to industries with low unionization rates. Both approaches indicate that RTW laws lower wages and unionization rates. Under the assumption that RTW laws only affect wages by lowering the unionization rate, RTW can be used as an instrumental variable (IV) to estimate the causal effect of unions on wages. In our preferred specification based on the differential exposure design, the IV estimate of the effect of unions on log wages is 0.35, which substantially exceeds the corresponding OLS estimate of 0.16. This large wage effect suggests that RTW may also directly affect wages due to a reduced union threat effect.

The purpose of this paper is to present a review of variance decomposition studies of firm performance and the theoretical foundations that served as the antecedents and promptings for this stream of research. Known collectively as “variance decomposition literature,” these studies use variance decomposition techniques to partition firm performance into various classes of effects in a bid to unveil the relative importance of factors responsible for firm performance variance.

A review of papers published in SCOPUS and institute for scientific information indexed journals was conducted.

The study found that firm, industry, corporate, business group and country effects are the major effects included in most extant studies. However, of all effects, firm effects remain the dominant and most important impact on firm performance. The effects that affect firm performance are also interdependent.

Consequently, the decisions of managers in firms are still the most important element in helping the firm to navigate industry and contextual factors, especially during periods of recession.

From the review, research gaps were identified and suggestions for future research provided. There is still much to learn from variance decomposition literature in an age of new business models, unprecedented start-up firms and from developing and emerging market countries.

An ongoing discussion in strategic management concerns the relative impact of specific strategic decisions on firm performance. In line with that tradition, this research seeks to analyze the relative impact of business domain choices on firm performance. More specifically, it aims to discuss a method of assessing the relative impact of firm and business domain effects on firm performance within a specific industry and to demonstrate the value of this method.

First, a model was developed to estimate the relative impact of firm versus business domain on performance. Second, all members of a specific SME‐dominated industry, namely the Belgian electrical wholesale sector, were questioned in order to test the validity of the developed model.

The results indicate that: the firms in the analyzed industry operate within two distinct business domains; and business domain effects explain from 6.8 percent to 9.7 percent of the variance in the included performance variables.

The findings should urge managers to carefully (re)consider where they are competing and assess the relative performance impact of business domain choices within their industry.

It is widely agreed that industry membership has performance implications. The effect of industry membership considers performance variation between industries. This, however, is one of the first studies to further analyze performance heterogeneity within an industry by considering the relative effect of business domain choices.

Literature, spanning industrial organization and strategic management disciplines, uses variance decomposition to understand the relative importance of firm, industry and business group effects in shaping profitability variations. Some literature analyzes firm profitability under transition to liberalization. Previous research has taken a static before-and-after view on institutional change. This paper aims to focus on the dynamic process of liberalization in India, analyzing how different institutional regime changes alter firm behavior leading to changes in profitability patterns.

Based on a panel data set of several thousand Indian firms, spanning the 26-year period between 1980-1981 and 2005-2006, the authors determine the relative importance of firm, industry and business group effects in explaining manufacturing firms’ profitability variances across different institutional phases. The authors evaluate three propositions that help assess transition dynamics between phases. They determine the quantum of catch-up or falling behind by firms.

Different industries emerge as profitability leaders, as the economy progresses through different liberalization phases. Business groups that have been more effective in resource appropriation, rent-seeking, politician management and non-market activities in a controlled regime are replaced as profit leaders by those that, in a free-market economy, can be capable of intra-business resource allocation tasks and leveraging corporate capabilities.

The approach demonstrates how to analyze the underlying detailed structure of firm-level data, and performance outcomes, to derive nuanced interpretation of factors giving rise to the effects that explain profitability variances, and how to assess the way these effects behave over time. The dynamic evidence-based approach highlights what factors matter, where, when and why, in influencing profitability variances, which are a key dimension of industrial and economic performance.

This paper aims to integrate insights from the behavioral theory of the firm and the dynamic capabilities perspective to explain how the historical and social attainment discrepancies motivate firms to change. Specifically, this paper proposes that a negative historical attainment discrepancy encourages the firm to engage in strategic change to solve its performance problems. In contrast, this paper advanced that a positive social attainment discrepancy motivates strategic change as a mechanism to bolster the firm’s position within the industry. Further, this paper integrated the moderating effects of industry dynamism and industry munificence.

This paper tests hypotheses using panel data on 2,435 US public firms over the years from 1996 to 2018. This paper uses a fixed-effects regression model to empirically test these hypotheses.

This paper finds empirical support for the effects of both the negative historical attainment discrepancy and the positive social attainment discrepancy on the firm’s tendency to engage in strategic change. As for the hypothesized moderating effects, this paper finds that industry munificence accentuated the effects of both attainment discrepancies on the firm’s tendency to engage in strategic change. However, the results do not support the hypothesized moderating effect of industry dynamism on either of these attainment discrepancies.

This paper contributes to the research on the separate effects of historical and social comparisons within the context of strategic change. Further, the paper bolsters our understanding of how performance feedback increases the firm’s tendency to change. Finally, the paper integrates theoretical views from the behavioral theory of the firm and the dynamic capabilities perspective on how socially high-performing firms may build and sustain their competitive advantage through organizational change.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

Using a sample of manufacturing firms listed in China between 2007 and 2019, first, this paper aims to examine whether peer firms influence corporate trade credit supply. Next, the authors examine the channels through which peer firms influence corporate trade credit supply by testing the predictions of rivalry and information theories. Furthermore, the authors examine the heterogeneity of the industry peer effect on corporate trade credit supply. Finally, the authors examine the economic consequences of the industry peer effect on corporate trade credit supply.

The sample includes all manufacturing firms listed on both the Shanghai and Shenzhen securities exchanges for the sample period from 2007 to 2019, and the data come from the China Stock Market & Accounting Research database. The authors use the fixed effects method to examine the industry peer effect on trade credit supply. The results are robust to a series of robustness tests. To address the potential endogeneity problem, the authors adopt appropriate instruments by estimating instrumental variable models (two-stage least square). The authors use Heckman’s two-stage model to mitigate the sample selection bias.

The authors provide strong empirical evidence showing that the industry peer effect on trade credit supply exists in the manufacturing sector. It is also found that both competitive rivalry-based and information-based theories can provide explanations of the industry peer effect on trade credit supply. This process is both active imitation and passive reaction. Additional analysis suggests that the industry peer effect on trade credit supply is more pronounced for state-owned firms, firms with low customer concentration and firms with high geographical proximity. The amplification effect and spillover effect are the economic consequences of the industry peer effect on trade credit supply. In other words, the trade credit supply based on peer effect will not only increase the liquidity risk of the firm per se but also induce and increase the liquidity risk of the industry.

The study makes some important contributions. First, the authors find robust evidence that peer firms’ trade credit supply is an important factor in explaining corporate trade credit supply, which extends the literature by connecting the firm’s trade credit supply with the peer effect. Second, the study provides a new micro-perspective for understanding that firms use trade credit supply as a tool of competition, which proves the importance of rivals’ decision-making as a determinant of corporate decisions. Third, the authors examine the industry peer effect on trade credit supply, which not only helps to guide firms to pay more attention to the potential risk and spillover effects of the trade credit supply decision-making relevance but also helps to clarify the industry interaction phenomenon of corporate decision-making behavior. It is an important practical significance to play a role as a bridge between the microlevel of the firm and the meso-level of the industry. Finally, the study provides inspiration for the formulation of industry norms and policies.

This study aims to elucidate the quantitative and qualitative differences in employment development between German districts. Building on ideas from competitive development and resource-based theory, the paper particularly seeks to explain enduring East-West differences between rural regions by two different forms of competitive advantage: cost leadership and quality differentiation.

This study follows a two-step empirical approach: First, an extended shift-share regression is conducted to analyze employment development in Western and Eastern German districts between 2007 and 2016. Second, the competitive share effect and other individual terms of the shift-share model are further examined in additional regressions using regional economic characteristics as exogenous variables.

The findings suggest that the above-average employment growth of the rural districts in the West is owed to the successful exploitation of experience in manufacturing that has been gathered by firms in the past 100 years or so. While their strategy is largely based on advanced and specialized resources and an innovation-driven differentiation strategy, the relatively weak employment development of Eastern rural districts might be explained by a lack of comparable long-term experiences and the related need to focus on the exploitation of basic and general resources and, accordingly, on the efficiency-based strategy of cost leadership.

This study offers an in-depth empirical analysis of how the competitive share effect, i.e. region-specific resources beyond industry structure, contributes to regional employment development. The analysis reveals that quantitative differences in rural employment development are closely related to qualitatively different levels of input factors and different regimes of competitiveness.