Search results

The authors analyzed the evolution of working from home (WFH) within industries in 12 European countries in the period 2008–2017 and studied its relationship with information and communication technologies (ICT).

The authors used data from the European Union Labour Force Survey (EU-LFS) to document the trends and levels of WFH within industries in 12 European countries. The authors further used the EU-KLEMS database and a difference-in-difference approach to study whether the fall in prices of ICT is associated with a higher share of employees who work from home in industries that depend more on ICT relative to industries that depend less.

The authors show that WFH has increased almost everywhere and that there is significant heterogeneity across industries. The authors provide evidence that the fall in prices of ICT is associated with a higher share of employees who work from home in industries that depend more on ICT relative to industries that depend less. This result also holds within age, gender and occupation groups. While the authors find no significant differences among gender and occupation groups, the positive association between the fall in ICT prices and WFH increases with age.

This paper has two main contributions: First, it reports that WFH has increased in European countries in the period 2008–2017. Second, it provides new explorations about the relationship between ICT and WFH by using the price variation of ICT.

This paper offers a new perspective on the potential motivation for the adoption of employee ownership based on market power. Employee ownership may be linked to market power, either through contributing to firm growth that leads to market power or through industry leaders adopting employee ownership as part of rent sharing or a broader consolidation of market position. Both employee stock ownership plan (ESOP) coverage and product market concentration (PMC) have been increasing in the past two decades, providing a good opportunity to see if and how these are related.

The authors predict ESOP adoption and termination using multilevel regressions based on 2002–2012 firm- and industry-level data from the Census Bureau, Compustat and Form 5500 pension datasets.

The authors find that the top four firms in concentrated industries are more likely to adopt Employee Stock Ownership Plans (ESOPs), while having an ESOP does not predict entering the top four, apart from firm-level predictors. Tests indicate the first result does not reflect simple rent sharing with employees but instead appears to reflect an effort by firms to consolidate market power through the attraction and retention (or “locking in”) of industry talent. Other positive predictors of ESOPs include company size, being in a high-wage industry and having a defined benefit (DB) pension.

To better distinguish among hypotheses, it would be helpful to have firm-level data on managerial attitudes, strategies, networks and monopsony measures. Therefore, future research using such data would be highly useful and encouraged.

The paper includes implications for the potential usefulness of ESOPs in attracting and retaining talent and for the design of nuanced policy to encourage more broadly based sharing of economic rewards.

While prior research focuses on firm-level predictors of employee ownership, this study uses market concentration and other industry-level variables to predict the use of ESOPs. This study makes a unique contribution, broadening the current thinking on firm motives and environmental conditions predictive of firm ESOP adoption.

As the global emphasis on environmental consciousness intensifies, many corporations claim to be environmentally responsible. However, some merely partake in “greenwashing” – a facade of eco-responsibility. Such deceptive behavior is especially prevalent in Chinese heavy-pollution industries. To counter these deceptive practices, this study aims to use machine learning (ML) techniques to develop predictive models against corporate greenwashing, thus facilitating the sustainable development of corporations.

This study develops effective predictive models for greenwashing by integrating multifaceted data sets, which include corporate external, organizational and managerial characteristics, and using a range of ML algorithms, namely, linear regression, random forest, K-nearest neighbors, support vector machines and artificial neural network.

The proposed predictive models register an improvement of over 20% in prediction accuracy compared to the benchmark value, furnishing stakeholders with a robust tool to challenge corporate greenwashing behaviors. Further analysis of feature importance, industry-specific predictions and real-world validation enhances the model’s interpretability and its practical applications across different domains.

This research introduces an innovative ML-based model designed to predict greenwashing activities within Chinese heavy-pollution sectors. It holds potential for application in other emerging economies, serving as a practical tool for both academics and practitioners.

The findings offer insights for crafting informed, data-driven policies to curb greenwashing and promote corporate responsibility, transparency and sustainable development.

While prior research mainly concentrated on the factors influencing greenwashing behavior, this study takes a proactive approach. It aims to forecast the extent of corporate greenwashing by using a range of multi-dimensional variables, thus providing enhanced value to stakeholders. To the best of the authors’ knowledge, this is the first study introducing ML-based models designed to predict a company’s level of greenwashing.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.

The present article draws from the behavioral theory of the firm, and it explores whether various dimensions of organization slack can be employed as variables to measure organizations’ antifragility during times of uncertainty such as the Covid-19 pandemic. Furthermore, considering the limitations and regulations put into place during the most recent pandemic, the present study seeks to explore the moderating effect that collaborative networks might have on the relationship between various dimensions of organizational slack and firms performance.

The present study retrieves data from Thomson Reuters Data Stream, and it gathers observations from manufacturing companies located in Europe. The dataset is composed of observations spanning from the fiscal year 2019–2022. Consequently, through the use of a balanced panel data, the authors conduct multiple regression analysis.

The obtained empirical findings reveal that high discretion slack has a positive effect on companies performance whereas low discretion slack has a negative effect on their performance. Additionally, the obtained findings indicate that low levels of reliance on collaborative networks positively moderates the relationship between organizational slack and firms’ performance. On the other hand, high levels of reliance on collaborative networks negatively moderate the relationship between organizational slack and firms performance.

This manuscript carries several original contributions. It expands the literature stream concerning antifragility and collaborative networks. Additionally, it postulates an operational measure which can be used to indicate firms’ antifragility.

Little is known about the determinants of supply chain finance (SCF) adoption among small and medium-sized enterprises (SMEs) in developing countries. This study aims to address this relevant research gap and hence, draws on the resource-based view and transaction cost economies to empirically investigate five factors that make SCF adoption practicable among SMEs in Ghana.

The approach involves a sample of 257 SME managers/owners and modelling via structural equations modelling.

All five factors (innovative capability, information sharing, inter- and intra-firm collaboration, external financing and trade process digitization) were found to impact positively and significantly on SCF adoption. The findings provide SME managers/owners with a research model which guides them on how to settle the SCF process.

This paper used a cross-sectional survey, which makes it impossible to access changes over time. In addition, the use of quantitative method limits respondents from expressing their feelings fully. Using a mixed or qualitative methodology will provide avenues for future research.

This paper offers a completive advantage for Ghanaian SMEs to strengthen their relationships while collaborating with each other. The findings suggest that by adopting SCF solutions, SMEs can optimize their liquidity and working capital. The factors underpinning SCF adoption are of incredible attractiveness for SME managers/owners to discover the relevant practice of SCF solutions. SMEs should adopt SCF strategies for improving their capability to respond promptly to transactions.

This paper is among the few papers that have examined these five factors in a developing economy context. The study also provides new understanding of the factors that influence SCF adoption in the context of a developing economy.

This study aims to utilise Six Sigma in an Irish-based red meat processor to reduce process variability and improve yields.

This is a case study within an Irish meat processor where the structured Define, Measure, Analyse, Improve and Control (DMAIC) methodology was utilised along with statistical analysis to highlight areas of the meat boning process to improve.

The project led to using Six Sigma to identify and measure areas of process variation. This resulted in eliminating over-trimming of meat cuts, improving process capabilities, increasing revenue and reducing meat wastage. In addition, key performance indicators and control charts, meat-cutting templates and smart cutting lasers were implemented.

The study is one of Irish meat processors' first Six Sigma applications. The wider food and meat processing industries can leverage the learnings to understand, measure and minimise variation to enhance revenue.

Organisations can use this study to understand the benefits of adopting Six Sigma, particularly in the food industry and how measuring process variation can affect quality.

This is the first practical case study on Six sigma deployment in an Irish meat processor, and the study can be used to benchmark how Six Sigma tools can aid in understanding variation, thus benefiting key performance metrics.

The authors extend the recent research using the risk component of human resource’s (HR’s) compensation plans to examine the effects of risk components on two strategic outcomes: within-firm temporal change, or strategic variation, and firm strategic divergence from the industry, or strategic deviation. In addition, the authors examine the role of previous financial performance as a boundary moderator condition of the effects of risk components in the compensation plan and firm strategic outcomes.

To examine the effects of low- and high-risk components of executive compensation on strategic variation and deviation over time, the authors collected data from 2,510 companies listed in the Standard and Poor’s 500 index in a panel data format of a 12-year period. The authors gathered financial and other firm-level data from COMPUSTAT, and executive compensation and executive-level data from ExecuComp.

The findings support the main effects of risk components on strategic change, while both high- and low-risk components act on strategic deviation contingent on the moderating role of total shareholder return (TSR). In the theoretical framework, the authors test the moderating role of total shareholder return (TSR) as a boundary condition of the effects of risk components in the compensation plan. In doing so, the authors provide a fine-grained understanding of the influence of compensation plan risk components on outcomes proximal to executives, such as the maintenance of the status quo and the search for financial gains.

New studies can explore a three-way moderating effect on performance indicators, such as TSR, Tobin’s Q and return on asset. The authors addressed this limitation and did a comparative analysis, but the authors did not include additional moderating mechanisms in these interactive effects.

By disaggregating the executive’s compensation based on the risk components, boards of directors can mitigate any possible unwanted biases in the relationship between principal and agent.

By considering the influence of both low- and high-risk components of compensation plans on strategic outcomes –instead of firm performance – this study expands strategy literature supporting the influence of compensation schema on a firm’s outcomes. This path is new because it offers a moderating perspective to understand the strategic deviations and changes that chief executive officers imprint in their firms.

Los autores amplían la investigación reciente usando el componente de riesgo de los planes de compensación de RH para examinar los efectos de los componentes de riesgo en dos resultados estratégicos: cambio temporal dentro de la empresa, o variación estratégica, y divergencia estratégica de la empresa de la industria, o desviación estratégica. Además, examinamos el papel del desempeño financiero anterior como una condición moderadora límite de los efectos de los componentes de riesgo en el plan de compensación y los resultados estratégicos de la empresa.

Para examinar los efectos de los componentes de alto y bajo riesgo de la compensación ejecutiva en la variación y desviación estratégica a lo largo del tiempo, recopilamos datos de 2510 empresas que figuran en el índice Standard & Poor's 500 en un formato de datos de panel de un período de 12 años. Los autores recopilaron datos financieros y de otro tipo a nivel de empresa de COMPUSTAT, y compensación de ejecutivos, y datos a nivel ejecutivo de EXECUCOMP.

Nuestros hallazgos respaldan los efectos principales de los componentes de riesgo en el cambio estratégico, mientras que los componentes de alto y bajo riesgo actúan sobre la desviación estratégica dependiendo del papel moderador del rendimiento total del accionista. En el marco teórico, los autores prueban el papel moderador del Retorno Total del Accionista como condición límite de los efectos de los componentes de riesgo en el plan de compensación. Al hacerlo, brindamos una comprensión detallada de la influencia de los componentes de riesgo del plan de compensación en los resultados próximos a los ejecutivos, como el mantenimiento del statu quo y la búsqueda de ganancias financieras.

al considerar la influencia de los componentes de bajo y alto riesgo de los planes de compensación en los resultados estratégicos, en lugar del desempeño de la empresa, este estudio amplía la literatura de estrategia que respalda la influencia del esquema de compensación en los resultados de una empresa. Este camino es nuevo porque ofrece una perspectiva moderadora para entender las desviaciones y cambios estratégicos que los CEOs imprimen en sus firmas.

los nuevos estudios pueden explorar un efecto moderador de tres vías en los indicadores de rendimiento, como TSR, Tobin's Q y ROA. Abordamos esta limitación e hicimos un análisis comparativo, pero no incluimos mecanismos moderadores adicionales en estos efectos interactivos.

al desagregar la compensación del ejecutivo en función de los componentes de riesgo, las juntas directivas pueden mitigar cualquier posible sesgo no deseado en la relación entre el principal y el agente.

Os autores estendem a pesquisa recente usando o componente de risco dos planos de remuneração de RH para examinar os efeitos dos componentes de risco em dois resultados estratégicos: mudança temporal dentro da empresa, ou variação estratégica, e divergência estratégica da empresa do setor, ou desvio estratégico. Além disso, examinamos o papel do desempenho financeiro anterior como uma condição moderadora dos efeitos dos componentes de risco no plano de remuneração e nos resultados estratégicos da empresa.

Para examinar os efeitos dos componentes de baixo e alto risco da remuneração executiva na variação e desvio estratégico ao longo do tempo, coletamos dados de 2.510 empresas listadas no índice Standard & Poor's 500 em um formato de dados de painel de um período de 12 anos. Os autores coletaram dados financeiros e de outros níveis da empresa da COMPUSTAT, remuneração executiva e dados de nível executivo da EXECUCOMP.

Nossos resultados suportam os principais efeitos dos componentes de risco na mudança estratégica, enquanto os componentes de alto e baixo risco atuam no desvio estratégico contingente ao papel moderador do Retorno Total ao Acionista. No referencial teórico, os autores testam o papel moderador do Total Shareholder Return como condição limite dos efeitos dos componentes de risco no plano de remuneração. Ao fazer isso, fornecemos uma compreensão refinada da influência dos componentes de risco do plano de remuneração nos resultados próximos aos executivos, como a manutenção do status quo e a busca por ganhos financeiros.

ao considerar a influência dos componentes de baixo e alto risco dos planos de remuneração nos resultados estratégicos -em vez do desempenho da empresa- este estudo expande a literatura de estratégia que apoia a influência do esquema de remuneração nos resultados de uma empresa. Esse caminho é novo porque oferece uma perspectiva moderadora para entender os desvios e mudanças estratégicas que os CEOs imprimem em suas empresas.

Novos estudos podem explorar um efeito moderador de três vias em indicadores de desempenho, como TSR, Q de Tobin e ROA. Abordamos essa limitação e fizemos uma análise comparativa, mas não incluímos mecanismos moderadores adicionais nesses efeitos interativos.

Ao desagregar a remuneração do executivo com base nos componentes de risco, os conselhos de administração podem mitigar possíveis vieses indesejados na relação entre principal e agente.

This study aims to investigate the variation in overvaluation proxies and volatility across industry sectors and time.

Using industry sector data from the S&P Capital IQ database, this study applies traditional cross-sectional regressions to investigate the relationship between overvaluation and volatility over the 2001–2020 time period.

This study finds that the most volatile industry sectors generally do not coincide with overvalued industry sectors in the cross-section, implying that there are limitations to price-multiple methods for forecasting future volatility. Rather, this study finds that historical volatility significantly increases the goodness-of-fit when modeling volatility in the cross section of industry sectors. The findings of this study imply that firms should increase disclosures and transparency about corporate practices to decrease downside risk that stems from bad news. In addition, the findings underline the consistency between market efficiency and high levels of volatility in periods of significant uncertainty.

This study proposes a novel approach to examining the cross section of volatility across time for industry sectors.

This study seeks to identify the main determinants of the optimal capital structure by reexamining the interpretation of the conventional set of explanatory variables used as proxies for the costs and benefits of debt in the context of the dynamic tradeoff theory.

The authors isolate the variation in leverage due to different targets from that caused by deviations by aggregating the data across a dimension identifying firms with similar targets – credit rating category.

Contrary to theoretical priors, large and profitable rated firms have lower targets. The authors show that size and profitability proxy for non-financial risk and that, for rated firms, non-financial risk is positively correlated to the optimal leverage. The benefits of a better rating outweigh the costs of foregone tax shields for firms with relatively low non-financial risk. The authors find support for that theory in institutional trading – institutional investors do not punish highly rated firms when credit downgrades occur.

This paper contributes to the capital structure literature by developing a new approach based on data aggregation. This study is the first, to the authors’ knowledge, to find a positive effect of the firm's non-financial risk on target leverage among rated firms. The authors argue that the benefit of a better credit rating is an increasing function of the rating itself. The authors also contribute to the literature on the impact of credit ratings on the capital structure choices of the firm.