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This study aims to focus on the role of labor regulation and credit market imperfections, in addition to that of factor endowments, in determining capital intensities in Indian manufacturing.

The paper considers an alternative approach to identifying the effects of India ' s labor regulations on industrial performance. In particular, the paper uses a measure of the stringency of labor regulations across countries – one that is completely independent of the India-specific measures used by earlier studies – and examines its relationship with capital intensities across manufacturing industries. Additionally, since labor regulations are unlikely to be the only reason for imperfections in factor markets, the paper also examines whether and to what extent capital market imperfections affect capital intensities across manufacturing industries. The paper then presents a case study that seeks to ascertain whether actual capital intensities prevailing in Indian manufacturing in major industry groups from 1989 to 1996 were larger than predicted capital intensities for these industry groups based on relative factor demand functions estimated for the USA (a country with relatively less restrictive labor laws and a more developed financial system) evaluated at Indian wages. Finally, the paper uses a recently available dataset to compare capital intensities in Indian and Chinese manufacturing to investigate the behavior of these two emerging Asian economies since 1980, when they started out with relatively similar socio-economic conditions.

The paper finds that India uses more capital-intensive techniques of production in manufacturing than countries at similar levels of development (and similar factor endowments), including China. For a majority of manufacturing industries, labor freedom and capital market development are, in addition to factor endowments, important determinants of capital intensity of production techniques used. Results reveal that, controlling for factor prices, India specializes in more capital-intensive varieties within broad industry groups relative to the USA, a more capital-abundant economy.

To the best of the authors ' knowledge, such a study has not been done for any other country. The paper sheds light on the important issue regarding the use of capital-intensive techniques in manufacturing in India, which is a labor-abundant country. The role of labor regulation has been extensively debated and the paper also investigates its role along with the role played by credit market imperfections.

Economic production analysis can provide critical perspectives on an industry’s performance. The purpose of this paper is to investigate the factor input intensity of hospitality and related industries, namely, accommodation, food service and amusement, gaming and recreation (AFAGR), compared to other service industries.

This paper compared AFAGR with other industries categorized as services by the North American Industry Classification System (NAICS). The NAICS code of up to four digits was used to collect data (US Census Bureau).

Results of this paper confirm extant literature that food service is more labor-intensive than other service industries; however, this was not true of accommodation and AGR industries. Similarly, while food service industry was relatively less intermediate input intensive than other service industries, accommodation and AGR were not. There were no significant differences between hospitality and other service industries (AFAGR) in their capital intensity. Another important finding was that while accommodation had constant results to scale, AGR had increasing returns to scale and food service industry was found to have decreasing returns to scale.

This investigation only looked at the four-digit NAICS-coded industries. International differences could also be investigated in the future.

Based on theoretical arguments, high labor intensity together with low intermediate input in food service industry suggests that efficiencies could be gained in these businesses. This may also be evident by the decreasing returns to scale that this paper found for the food service industry. These comparisons could guide additional research about the causes, consequences and potential sources of improvement of efficiency of economic productivity in AFAGR. Managers in AFAGR would find it valuable to understand how they might be able to enhance economic output, particularly in the context of the role of labor. Furthermore, any changes in one economic input would have implications on other inputs and possibly on productivity.

Any future recalibration of input intensity in hospitality industries could have both social and economic consequence.

This paper enhances our understanding of how hospitality industries use economic factors of production. Labor in AFAGR is viewed as a given. This study suggests that food service industry may need to reevaluate its labor productivity, the way it is measured and how it might affect efficiencies. Such understanding could better inform the sources and causes of economic efficiencies in AFAGR industries. Until now, this understanding has mostly been based on relatively scarce comparative systematic analysis.

Research based on Bangladesh–US trade data examines the Heckscher–Ohlin model and the Rybczynski hypothesis in this study.

Ordinary least square (OLS) techniques are used in this study, which relies on data from the NBER International Trade and Geography Data and the UN Comtrade Database for the years 2018 and 2008.

The research shows that trade between the United States and Bangladesh follows Heckscher–Ohlin and Rybcyzinski's trade predictions. According to the study, since labor is in plentiful supply in Bangladesh, Bangladesh's labor-based sectors have a higher US labor-to-capital import shares than US capital-based industries. As Bangladesh has not changed significantly from a labor-based country since 2008, it retains the same pattern even though the share of US unskilled labor-based sectors imported from Bangladesh decreased in 2018.

The findings of this study have a wide range of implications for both trade theory and policy debates between Bangladesh and the United States.

This study aims to explore the strategic impact of R&D and export activity on the diverse dimensions of US manufacturing firms’ performance. It also explores, using a predictive analytic model, the interactive synergistic effect that R&D and exports have on firm performance.

This study presents an innovative two-stage regression-neural network approach. Complementing conventional statistical analysis, the predictive backpropagation neural network explores the relative impact of R&D and exports and their synergistic effect on firm performance.

This study demonstrates the significant and positive effect of R&D and export strategy/activity on the economic performance of leading US manufacturing firms, particularly on their market-based performance (i.e. sustained growth rate or SGR). Furthermore, this study finds that the synergistic effect of R&D and exports on short-term performance (i.e. return on investment) is positive in high-tech firms but negative in low-tech firms. However, the synergistic effect on SGR is increasingly positive regardless of the level of technology.

In addition to traditional statistical analysis, this study uniquely investigates the relative importance of selected strategic variables, along with R&D and export activity and their differential synergistic effects, for firms’ economic performance in contrasting industry settings (high-tech vs low-tech).

This study aims to predict China's carbon emission intensity and put forward a set of policy recommendations for further development of a low-carbon economy in China.

In this paper, the Interaction Effect Grey Power Model of N Variables (IEGPM(1,N)) is developed, and the Dragonfly algorithm (DA) is used to select the best power index for the model. Specific model construction methods and rigorous mathematical proofs are given. In order to verify the applicability and validity, this paper compares the model with the traditional grey model and simulates the carbon emission intensity of China from 2014 to 2021. In addition, the new model is used to predict the carbon emission intensity of China from 2022 to 2025, which can provide a reference for the 14th Five-Year Plan to develop a scientific emission reduction path.

The results show that if the Chinese government does not take effective policy measures in the future, carbon emission intensity will not achieve the set goals. The IEGPM(1,N) model also provides reliable results and works well in simulation and prediction.

The paper considers the nonlinear and interactive effect of input variables in the system's behavior and proposes an improved grey multivariable model, which fills the gap in previous studies.

Moral intensity is the degree of feeling we have about the consequences of moral choices, similar, for example, to those perceived for crimes, from petty larceny to murder. Moral intensity is thought to increase moral sensitivity and judgment. Because the accounting professions require members to respond to accounting fraud with more sensitivity and intensity, we examine this response in 220 professional accountants (mostly Certified Public Accountants) under a controlled experiment using two different cases. We examine the first three parts of the Rest (1986) model including ethical evaluation, judgment, and intention to act. We measure moral intensity in the accountant’s perception of overall harm and societal pressure. As in prior research, we find that the degree of moral intensity may be contextual. We find that the ethical evaluations may become affected by perceived overall harm, and whistleblowing intentions by perceived societal pressure. However, in both cases, the professional’s judgments are most affected by moral intensity. Consistent with prior research, whistleblowing intentions may involve many other mitigating variables, such as audit reporting or non-audit reporting limited by codes of conduct. These findings relate to the increasing attention paid by the SEC to finding accounting fraud.

This manuscript makes three important contributions to the existing literature. First, there are few studies in this area and Jones (1991) identifies that moral intensity is issue contingent; therefore, replication studies using different scenarios are needed. Second, Bailey, Scott, and Thoma (2010) have suggested that accounting ethics research has focused too narrowly on Component II of Rest’s Four-Component Model. None of the previous studies looked at all three steps in Rest’s Model; therefore, our manuscript provides an important contribution over the other previous studies. Third, our sample uses professionals and not students as surrogates for professionals.

Purpose: Mentioning a criminal’s country of origin in crime news is a divisive and much-discussed issue among both journalists and members of society. Scholars assume that mentioning a criminal’s foreign origin could develop and maintain prejudices against individuals with a migrant background among news recipients. However, until now, no attention has been paid to what increases the likelihood that a journalist does or does not mention a criminal’s country of origin when reporting on crimes. Methodology/approach: One possible explanation is that the frequency and intensity of specific news factors could lead to mentioning a criminal’s origin, since increased importance of a news story is usually assigned when many high-intensity news factors occur. Even though numerous studies have determined the frequency of specific news factors in (crime) news, the explanation hypothesized in this chapter has not yet been examined. To investigate this supposition empirically, a quantitative content analysis of four German prime newscasts (n = 290), including public and private broadcasts, was conducted in the current study. Findings: The findings indicate that mentioning criminals’ origins is still common practice in journalism; furthermore, criminals with foreign origins are explicitly represented as foreign almost ten times more often than German-origin criminals are explicitly mentioned as German. News factors such as personalization, location, and influence show some effects of positively predicting journalistic mentioning of a criminal’s country of origin.

The purpose of this paper is to consider corporate social irresponsibility (CSI) within the supply chain. The discussion focuses on the social component of social responsibility and explores its effects on end-users. Moreover, this paper presents moral intensity, a construct introduced in the ethics literature, as a potential guide to managers who struggle to navigate the gray area between corporate social responsibility (CSR) and CSI.

This paper conceptualizes CSI within the supply chain and offers a framework and propositions for understanding and preventing irresponsible behavior from a moral intensity perspective.

The moral intensity framework provides a normative approach with the potential to guide managers who face choices involving decisions that might lead to irresponsible behavior in interorganizational settings.

This paper draws attention to business-to-business CSI and the limited research that focuses on the social aspects of CSR, rather than the environmental and economic factors emphasized in prior research. It also introduces the moral intensity framework to the supply chain literature and highlights the end-user’s (i.e. consumer’s) role in influencing the performance of the overall value chain.

The purpose of this paper is to identify the intra-organizational factors effective in a successful strategy implementation, measure the interaction intensity, analyze relation patterns among those factors, and lastly, prioritize the factors according to the level of importance and effect in the success of a strategy implementation.

A review of the literature produced 13 key intra-organizational factors involved in successful strategy implementation. The factors were then prioritized and the interaction among them was identified using interpretive structural modelling (ISM). DEMATEL was employed to quantitatively calculate the importance, intensity and effect in the interaction among the factors. Finally, combining both the aforementioned methods an integrated ISM-DEMATEL model was devised through which the factors were prioritized while the importance, intensity and effect of each factor were quantitatively calculated.

Prioritization and establishing relations and interactions among the identified factors by ISM; determining the priority of each factor and their intensity of effect and interaction on a quantitative basis through DEMATEL method and developing the integrated model of ISM-DEMATEL for intra-organizational factors effective in successful strategy implementation.

Due to time limitation, the hybrid model could not be practically applied to any organizations or businesses and in this research, only 12 experts were consulted to construct the model. If the experts involved were increased both quantitatively and qualitatively no doubt the final model would be upheld.

Managers who are involved in strategy implementation or who intend to enter this phase are advised to apply the integrated ISM-DEMATEL model that presented in this paper in order to obtain good perspective about interaction and prioritization among the intra-organizational factors effective in strategy implementation success.

Identification of 13 key intra-organizational factors effective in successful strategy execution, by studying through the literature; prioritization and establishing relations and interactions among the identified factors by ISM; determining the priority of each factor and their intensity of effect and interaction on a quantitative basis through DEMATEL method; developing the integrated model of ISM-DEMATEL for intra-organizational factors effective in successful strategy execution; improving the integrated model through ISM by applying the findings obtained through DEMATEL.

The paper aims to investigate the effects of several determinants of firm import intensity in US foreign trade zones (FTZs). Even though the major objective for the establishment of US FTZs is to encourage exports by facilitating the duty-free entry of imports, US firms have used it as a gateway to import goods into the US market. Currently, over 90 per cent of US FTZ output is consumed in the USA. The author examines the major determinants for such import intensity in US FTZs.

The study is based on a survey that was conducted to explore the factors that influence import intensity of firms operating in US FTZs.

The findings reveal that besides export orientation of firms, the most promising predictors of import intensity of firms operating in USA FTZs are the policy environment in the form of inverted tariff benefits and firm business strategy.

The findings are important for managers presently operating in US FTZs or intend to do so in future.

Even though there are numerous studies on free trade zones and exports, this is the first study to examine the import intensity of US FTZs and their determinants.