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The purpose of this paper is to determine if there is a link between corporate shareholder value creation and economic growth. The first objective of this paper is to determine which specific shareholder value measurement best explains shareholder value creation for a particular industry. The next objective of the study is to establish, for each of nine different categories of firms examined, a set of value drivers that are unique and significant in expressing shareholder value for that particular category of firms. Lastly, the relationship between shareholder value creation and economic growth is tested.

To quantify and measure value creation, the paper investigates the various value creation measurements that are being applied. The next step is to ascertain whether various industries have different value creation measures that best explain value creation for the respective industries. Then, the value drivers of these specific value creation measures can be determined and their relationship with economic growth tested.

The results of this study indicate that each industry does have a specific shareholder value creation measurement that best explains shareholder value creation for that industry; for example, for five of the nine categories (industries) that were analyzed, market value added was found to be the best shareholder value creation measurement, but for capital-intensive firms and manufacturing firms, the Qratio is the best measure, while for the food and beverage industry, the market to book ratio was found to be a better measure of shareholder value creation than other measures tested. It was further found that an increase in corporate shareholder value creation is to the detriment of economic growth.

The contribution of the present study is its determination of a unique shareholder value creation measurement for particular industries. In addition, a specific set of variables per industry that create shareholder value is identified. Lastly, the important link between shareholder value creation and economic growth is exposed.

This study aims to enrich the current theoretical debate on the growth of start-up firms by extensively investigating the ongoing empirical studies in this research stream. Moreover, this study identifies drivers whose support roles are confirmed in the literature and recommends further research opportunities.

In this study, we analysed the results of 316 empirical studies on start-up firms and growth and also identified and categorised 66 growth drivers. We presented these drivers in three-dimensional charts: 1) the frequency of using each driver in the 316 studies, 2) the consistency of each driver as measured by the number of studies supporting its statistical significance and 3) the net effect (positive or negative) of each driver on growth.

Our analysis compares extant studies on growth drivers and shows some under-explored growth factors of start-up firms.

Both start-up managers and policymakers can benefit from this study. This study provided managers with a fine-grained tool on the main growth drivers and can guide policymakers in supporting policies for start-up firms.

This study provides a rich, fine-grained and coherent picture of several potential growth drivers of start-up firms. Moreover, we extended our analysis to various potential drivers more than previous studies on this topic, thereby providing fruitful insights into the critical growth factors for start-up firms.

Enterprise systems are commonly implemented by firms through outsourcing arrangements with software vendors. However, deriving benefits from these implementations has proved to be a challenge, and a great deal of variation has been observed in the extent of value generated for client and vendor firms. This research examines the role of co-specialization as a strategy to make the most out of outsourced enterprise systems. The authors develop hypotheses relating resource co-specialization with two indicators of success for implementation of enterprise software: (1) exchange success and (2) firm growth.

The hypotheses are tested using a unique panel data set of 175 firms adopting Advanced Planning and Scheduling (APS) software, a type of enterprise system used for managing manufacturing and logistics. The authors identify organizational factors that support co-specialization and then examine how co-specialization is associated with enterprise software implementation success, controlling for the endogenous choice to co-specialize.

The empirical results suggest that resource co-specialization is positively associated with implementation success and that the two resource co-specialization pathways that are examined complement each other in providing performance benefits.

This paper contributes to the research literature on outsourcing. The study also provides a new empirical test using a unique data set of 175 firms adopting APS Software.

This paper aims to study the determinants of private investment in Egypt while accounting for uncertainty associated with financing decisions of the firm using time series analysis over the period 1982-2015. The analysis is based on Tobin’s (1969) Q-theory of investment. The variables used in the empirical model are investment rate, average q index, prices of capital goods, internal finance and external finance.

This research is concerned with the model specification of a dynamic Average Q model. In that respect, the current research describes the data, presents the empirical methodology and estimates the Average Q model of investment and obtains the results. The empirical procedures and results of studying the average Q model. It includes testing for the unit root in the time series, vector error correction model (VECM) and cointegration long run analysis, and finally estimations of the model under uncertainty and empirical results.

Stochastic shocks to the determinants of private investment in Egypt have their impact on investment rate. The representation of impulse response in VECM shows that a one standard deviation shock to the value of the firm has a positive impact on investment rate. Stochastic shocks to both internal finance and external finance have slightly positive response from investment rate. Also, a stochastic shock to investment rate has a positive yet declining response from itself. However, a stochastic shock to prices of capital goods has a negative impact on investment rate. The representation of variance decomposition in VECM shows that investment rate is positively affected yet at a declining rate by a one standard deviation shock in both internal and external finance during the period 1982-2015. Also, a stochastic shock in the value of the firm or in the prices of capital goods has a slightly positive impact on investment rate.

Investment and capital accumulation are the main vehicles for economic growth and development. There have been fluctuations in Egypt’s investment rates since mid-1970s due to variations in saving rates. Thus, it is important to present some policy implications that could potentially assist the enhancement of the Egyptian economy. In that respect, the estimated results of the empirical model show that changes in the prices of capital goods in Egypt are significant factors that have negative impact on investment rate. Prices of imported capital goods in Egypt are affected by foreign exchange market conditions in the form of significant changes in the pound exchange rate. Thus, foreign exchange market reforms, as adopted recently in the Egyptian economy and improvements in trade balance, are important steps to alleviate obstacles that hinder investment. Regarding the source of finance, the estimated results showed that changes in both internal and external finance have a positive impact on investment rate. In this case, it is the firm’s decision to choose the method of financing its investment depending on factors such as its market value, institutional size and capacity and the opportunity cost of the funds used in financing the required investment.

This paper aims to demonstrate methods that sustainability-conscious brands can use to include their primary producers in the measurement and reporting of the environment and sustainability performance of their supply chains. It explores three questions: How can farm businesses provide information required in sustainability reporting? What are the challenges and opportunities experienced in preparing and presenting the information? What future research and policy instruments might be needed to resolve these issues.

This study identifies and describes methods to provide the farm-level information needed for environmental performance and sustainability reporting frameworks. It demonstrates them by compiling natural capital accounts and environmental performance information for two wool producers in the grassy woodland biome of Eastern Australia; the contrasting history and management of these producers would be expected to result in different environmental performances.

The authors demonstrated an approach to NC accounting that is suitable for including primary producers in environmental performance reporting of supply chains and that can communicate whether individual producers are sustaining, improving or degrading their NC. Measurements suitable for informing farm management and for the estimation of supply chain performance can simultaneously produce information useful for aggregation to regional and national assessments.

The methods used should assist sustainability-conscious supply chains to more accurately assess the environmental performance of their primary producers and to use these assessments in selective sourcing strategies to improve supply chain performance. Empirical measures of environmental performance and natural capital have the potential to enable evaluation of the effectiveness of sustainability accounting frameworks in inducing businesses to reduce their environmental impacts and improve the condition of the natural capital they depend on.

Two significant social implications exist for the inclusion of primary producers in the sustainability and environmental performance reporting of supply chains. Firstly, it presently takes considerable time and expense for producers to prepare this information. Governments and members of the supply chain should acknowledge the value of this information to their organisations and consider sharing some of the cost of its preparation with primary producers. Secondly, the “additionality” requirement commonly present in existing frameworks may perversely exclude already high-performing producers from being recognised. The methods proposed in this paper provide a way to resolve this.

To the best of the authors’ knowledge, this research is the first to describe detailed methods of collecting data for natural capital accounting and environmental performance reporting for individual farms and the first to compile the information and present it in a manner coherent with the Kering EP&L and the UN SEEA EA. The authors believe that this will make a significant contribution to the development of fair and standardised ways of measuring individual farm performance and the performance of food, beverage and apparel supply chains.

With China’s economic growth slowing down and the growth rate of fiscal revenue decreasing, the pressure on local government debts is further increasing. Under this background, it is of great significance to clarify the relation between local government debts and China’s economic growth in order to give full play to the positive role of local debts in stabling growth. The paper aims to discuss this issue.

Therefore, this paper explores the impact of Chinese local government debt on economic growth from theoretical and empirical aspects, respectively, and compares the regional differences between different debts and economic growth dynamics.

In the theoretical model part, this paper constructs a three-sector dynamic game model, under the two circumstances of whether local government is subject to debt constraints, and examines the relation between local government debt and economic growth and other variables through numerical simulation. Research shows that when the government is not constrained by debt, there is an inverted “U” relation between government debt and economic growth. When the government is constrained by debt, the economic growth rate gradually decreases as the government debt increases.

In the theoretical analysis part, this paper tries to estimate the amount of local debts under different calibers and examines the impact of different types of local government debts on China’s economic growth and their regional differences. The results show that excessive accumulation of government hidden debts in the eastern region is not conducive to economic growth, while explicit debts in the central and western regions significantly contribute to local economic growth. The results of empirical analysis are basically consistent with the predictions of the theoretical model.

This paper aims to analyze the influence of organizational learning (OL) and service innovation (SI) on organizational performance of knowledge-intensive business services (KIBS) and examine the mediating role of SI.

Hypotheses were tested using the theoretical OL model of knowledge acquisition, distribution, interpretation and organizational memory (Huber, 1991; Lopez, Peon, & Ordas, 2005; Jiménez-Jiménez & Sanz-Valle, 2011), using structural equation modeling partial least squares analysis of a survey data set of Brazilian architectural firms.

Findings suggest that OL is significantly linked to SI and so is SI to organizational performance. However, neither the direct relationship between OL and organizational performance could be verified, nor the mediating effect of SI.

These results can offer KIBS managers insights that suggest that OL alone does not guarantee a significant impact in organizational performance, but it is a starting point for achieving SIs, that lead to performance improvement and competitive advantages.

This paper contributes to the knowledge production in the following ways: to the understanding of the relationship between OL and SI and its effect on organizational performance, traditionally overlooked in the literature; to the study of SIs, considering the importance of the service sector; and to the study of innovation processes in architectural firms, a sector traditionally understudied, because of the focus on large construction firms.

To cope with the severe situation of the global climate, China proposed the “30 60” dual-carbon strategic goal. Based on this background, the purpose of this paper is to investigate scientifically and reasonably the interprovincial pattern of China’s power carbon emission intensity and further explore the causes of differences on this basis.

Considering the principle of “shared but differentiated responsibilities,” this study measures the carbon emissions within the power industry from 1997 to 2019 scientifically, via the panel data of 30 provinces in China. The power carbon emission intensity is chosen as the indicator. Using the Dagum Gini coefficient to explore regional differences and their causes.

The results of this paper show that, first, China’s carbon emission intensity from the power industry overall is significantly different. From the perspective of geospatial distribution, the three regions have unbalanced characteristics. Second, according to the decomposition results of the Gini coefficient, the overall difference in power carbon emission intensity is generally expanding. The geospatial and economic development levels are examined separately. The gaps between the eastern and economically developed regions are the smallest, and the regional differences are the source of the overall disparity.

Further exploring the causes of differences on this basis is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies. This study provides direction for analyzing the green and low carbon development of China’s power industry.

As an economic indicator of green and low-carbon development, CO₂ intensity of power industry can directly reflect the dependence of economic growth on the high emission of electricity and energy. and further exploring the causes of differences on this basis is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies.

For a long time, with the rapid economic development, resulting in the unresolved contradiction between low energy efficiency and high carbon emissions. To this end, scientifically and reasonably investigating the interprovincial pattern of China’s power carbon emission intensity, and further exploring the causes of differences on this basis, is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies.

Third, considering the influence of spatial factors on the convergence of power carbon emission intensity, a variety of different spatial weight matrices are selected. Based on the β-convergence theory from both absolute and conditional perspectives, we dig deeper into the spatial convergence of electricity carbon emission intensity across the country and the three regions.

The paper aims to explore the effect of stakeholder pressure on the disclosure of key performance indicators (KPIs) and the patterns of this disclosure in large public interest entities (PIEs).

The study is based on the content analysis of the disclosures provided by 169 large (PIEs) operating in Poland in 2019. The data was hand-collected from the companies’ non-financial statements. The research hypotheses were empirically tested with the use of linear regression.

The explanation for the disclosure of KPIs can be found in stakeholder theory, operationalized by stakeholder pressure linked to industry. In line with the expectations, business-related KPIs are disclosed by companies operating in industries with high pressure from investors, environment-related KPIs are presented by companies operating in environmentally sensitive industries and companies operating in industries with high pressure from employees disclose society-related KPIs. According to the results of the study, reporting on employee-related KPIs is accompanied by environmental and social KPI disclosures.

The study contributes to the literature on corporate non-financial disclosures as it provides new insights into non-financial KPI disclosures in a new and relatively unexplored institutional setting established by the Directive 2014/95/EU. While researchers recognize the stakeholders’ environmental and social concerns, there is nevertheless a lack of understanding of their implications for KPIs in measuring social practice. The research fills that gap by addressing the specific impact of different stakeholder groups on the disclosure of KPIs.

The main aim of this paper is to examine the claim that economic value added (EVA) advocates its superiority over the traditional accounting-based financial performance measures, i.e. profit after tax (PAT), earnings per share (EPS), return on assets (ROA), return on equity (ROE) and return on investment (ROI) in the Indian manufacturing sector and at the same time, give empirical facts. It also tests and examines the information content of various performance measures and their relationship with stock returns.

The paper uses the sample of 534 Indian manufacturing companies from the Bombay Stock Exchange (BSE) during the period 2000–2018. Multiple regression models are applied to examine the information content of EVA and traditional performance measures in explaining shareholders’ returns.

Relative information content tests revealed that traditional accounting-based measures such as EPS, ROE and ROA performed better than EVA in explaining the returns of Indian manufacturing companies. Incremental information content of EVA adds little contribution to information content above traditional performance measures. The claim of superiority of EVA over accounting-based measures in association with shareholder returns is proved invalid in Indian manufacturing companies.

This study concludes that EVA has no superiority over traditional accounting-based financial performance measures in explaining stock returns of Indian manufacturing companies. To achieve heftiness in outcomes, panel data are tested by using Breusch–Pagan–Godfrey (BPG) test for heteroskedasticity, Hausman’s test for fixed and random effect, variance inflation factor (VIF) test for multicollinearity and Durbin–Watson test for autocorrelation.