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This study aims to investigate the impact of stakeholders’ nonfinancial resources (NFRs) on companies’ profitability, filling a significant gap in the literature regarding the role of NFRs in value creation.

Data from 76 organizations from 2017 to 2019 were collected and analyzed. Four primary NFRs and their key value drivers were identified, representing core elements that support different dimensions of a company’s performance. Statistical tests examined the relationship between stakeholders’ NFRs and financial performance measures.

When analyzed collectively and individually, the results reveal a significant positive influence of stakeholders’ NFRs on a firm’s profitability. Higher importance assigned to NFRs correlates with a higher return on sales.

This study contributes to the literature by empirically bridging the gap between stakeholder theory and the resource-based view, addressing the intersection of these perspectives. It also provides novel insights into how stakeholders’ NFRs impact profitability, offering valuable implications for research and managerial practice. It suggests that managers should integrate nonfinancial measures of NFRs within their performance measurement system to manage better and sustain companies’ value-creation process.

In response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.

An automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.

The docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.

The proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

Supply chain revamping (SCR) is an important strategy for firms to improve their supply chain operations in a rapidly changing environment. The purpose of this study is to shed light on the impact of SCR on shareholder value.

Based on Signaling Theory and 184 SCR announcements published by US-listed firms from 2013 to 2018, this study employs event study methodology and empirically examines three issues: Antecedents of SCRs; Primary purposes and actions of SCRs; In addition to the impact of SCRs on shareholder value using stock returns, we also examined the factors that can influence the extent of stock returns.

Firstly, our results indicate that SCRs are primarily driven by firms’ poor prior performance, CEO turnover and external control threats (ECTs). Secondly, the stock market favors SCRs aiming to meet customer needs and those accomplished through network remodel. However, the market reacts negatively to SCRs aiming at cutting costs, improving poor performance, and those implemented through network trim. Finally, the cross-sectional analysis indicates that shareholders prefer firms operating in more competitive or faster-growing industries and those adopting an expansionist strategy than those adopting a streamlining strategy.

Our study provides managers with valuable insights into when firms can benefit from initiating SCRs not only by examining the purposes and actions of SCRs but also by examining the industry- and strategy-specific moderators. Our study illuminates the conditions under which SCR will positively affect shareholder value. Additionally, this study contributes to the existing literature by deepening the understanding of the impact of supply chain decisions on firm performance and identifying the marginal conditions under which the stock market will react positively to SCR announcements.

We examine how superstition shapes corporate tax avoidance and do so by taking a risk perspective and focusing on the zodiac-year belief prevalent in China.

We adopt a difference-in-differences research design to compare the degree of corporate tax avoidance in the CEOs’ zodiac year with that in the adjacent years. We do propensity-score matching to form a sample of Chinese listed firms for the regression analysis.

We find causal evidence that firms exhibit a greater magnitude of tax avoidance in the CEOs’ zodiac years, a result attributable to relatively weak tax enforcement in the Chinese context. We also find that the zodiac-year effect on corporate tax avoidance is more pronounced for firms with tight financial constraints, firms with high business risk, firms headquartered in regions with a high degree of superstition and non-state-owned firms.

This study is the first to show that superstition is a determinant factor of tax avoidance and contributes to the tax literature by shedding light on the behavioral risk factors that shape corporate tax avoidance. We take the perspective of CEOs’ risk appetite to analyze how tax avoidance is influenced by the CEOs’ trade-off between the costs and benefits of avoiding taxes. Our results suggest that, when CEOs are more risk-averse, they attach more importance to financial risk than the risk of reputational losses and litigation associated with corporate tax avoidance. The findings imply that tax avoidance can be curbed by increasing (or decreasing) the tax (financial) risk confronting the CEOs.

The objective of this study is to explore the structural attributes of the pharmaceutical industry before the onset of the COVID-19 pandemic by examining the relationship between inventory and firm performance and developing a taxonomy of pharmaceutical firms based on the earns-turns matrix.

This study examines the inventory–firm performance linkage, considering both total inventory and its discrete inventory components in pharmaceutical firms. In addition, this research develops a new taxonomy of pharmaceutical firms based on the earns-turns matrix. A large panel dataset of firms in the US pharmaceutical industry was collected for the period 2000–2019.

The results reveal that strategic groups identified based on this taxonomy show different levels of profitability and inventory turns in the earns-turns matrix. Most pharmaceutical firms moved from the low-right to the top-left section in the earns-turns matrix, indicating that these firms have generally pursued profitability rather than effective inventory management.

This study explores the structural attributes of the pharmaceutical industry using the earns-turns matrix. This two-dimensional analysis may not, however, capture the full complexity of inventory–firm performance dynamics.

The mapping of strategic groups on the earns-turns matrix provides a useful tool for visual representations of the dynamics of strategic groups in terms of financial performance and inventory management performance. Practitioners can use the earns-turns matrix to benchmark their firm's position against their competitors.

This study broadens the scope of operations management research by introducing the earns-turns matrix as an empirical validation tool for operational and strategic management theories. This study emphasizes the effectiveness of the earns-turns matrix in analyzing strategic groups of pharmaceutical firms.

Asset maintenance in manufacturing industries is a critical issue as organizations are highly sensitive towards maximizing asset uptime. In the advent of Industry 4.0, maintenance is increasingly becoming technology driven and is being termed as Maintenance 4.0. Several barriers impede the implementation of Maintenance 4.0. This article aims at - exploring the barriers to implementation of Maintenance 4.0 in manufacturing industries, categorizing them, analysing them to prioritize and suggesting the digital technologies to overcome them.

Twenty barriers to the implementation of Maintenance 4.0 were identified through literature survey and discussion with the industry experts. The identified barriers were divided into five categories based on their source of occurrence and prioritized using fuzzy-technique for order preference by similarity to ideal solution (TOPSIS), sensitivity analysis was carried out to check the robustness of the solution.

“Data security issues” has been ranked as the most influencing barrier towards the implementation of Maintenance 4.0, whereas “lack of skilled engineers and data scientists” is the least influencing barrier that impacts the implementation of Maintenance 4.0 in the manufacwturing industries.

The outcomes of this research will help manufacturing industries, maintenance engineers/managers, policymakers, and industry professionals for detailed understanding of barriers and identify easy pickings while implementing Maintenance 4.0.

Manufacturing industries are witnessing a paradigm shift due to digitization and maintenance 4.0 forms the cornerstone. Little research has been carried in Maintenance 4.0 and its implementation; this article will help in bridging the gap. The prioritization of the barriers and digital course of actions to overcome those is a unique contribution of this article.

This paper aims to examine the consequences of board diversity (BD) in Kuwait. In particular, it examines the impact of BD (gender, age and nationality) on earnings management (EM).

The research uses data from 103 non-financial Kuwaiti-listed companies from 2010 to 2017. The data is collected from the companies’ data from secondary sources such as their annual reports. The data analysis methods are correlation, multi-regression and robust regression. EM is measured using the modified Jones model (1995) and Kothari et al. (2005).

The findings show a negative association between gender diversity (GD) and EM. It also found a positive relationship between age diversity (AD) and EM and no relationship between national diversity (ND) and EM.

This study’s results have significant implications for investors. The practical empirical findings indicate that GD on the board did not impact on EM. Also, it is more important to have senior directors on the board than AD to reduce EM. There is no need to employ any foreigners because they do not affect EM.

It contributes to the growing body of literature on BD by investigating its effect on EM. Furthermore, building on the broader literature on gender, age and ND by highlighting the critical role that women, young people and foreign directors play in improving boards' monitoring role on EM. More specifically, it contributes to existing knowledge, provides a theoretical contribution and makes a methodological contribution.

This study aims to evaluate the effectiveness of tax incentives provided by the Ethiopian government in spurring private investment and job creation, using unique administrative and survey data.

The study employs a dataset covering large- and medium-scale manufacturing in Ethiopia from 2012 to 2018, combined with administrative data on actual tax payments and statutory obligations to gauge the impact of tax incentives. Regression analysis using the generalized method of moments (GMM) is used to examine the relationship between tax incentives and employment, taking into account variations in production, distribution and financial costs.

The study finds that tax incentives do not significantly affect employment at conventional significance levels. The incentive elasticity of employment appears to diminish as production, distribution and financial costs increase. Consequently, the incentives provided by the government have not had a substantial impact on employment generation within the manufacturing sector.

This study is unique for its comprehensive analysis of tax incentives in the Ethiopian manufacturing sector using both administrative and survey data. It highlights that increasing production and financial costs can offset the employment benefits of these incentives, emphasizing the need for a more favorable business environment for private investors.

Research indicated that dietary antioxidants could improve immune system performance. This study aims to investigate the association of COVID-19 symptoms, total antioxidant capacity and serum inflammatory markers, with dietary antioxidants intake among angina patients.

A food frequency questionnaire was used in a cross-sectional study among 135 angina patients with COVID-19, to assess dietary antioxidants consumption. Serum levels of tumor necrosis factor, interleukin 1ß, malondialdehyde, high-sensitivity C-reactive protein and total antioxidant capacity were measured by enzyme-linked immunosorbent assay methods.

Among study angina patients, 76.67% followed unhealthy food patterns and 23.33% followed anti-inflammatory dietary patterns before hospitalization. The angina patients with anti-inflammatory food pattern had less fever (p = 0.021), cough (p = 0.018), dyspnea (p = 0.024), diarrhea (p = 0.014) and pneumonia severity index (p = 0.014) compared to patients with unhealthy food pattern. The serum levels of tumor necrosis factor, interleukin 1ß, high-sensitivity C-reactive protein and malondialdehyde, had a significantly negative association with dietary antioxidants intake (p < 0.05).

There are significant association between antioxidant intake with serum inflammation markers in COVID-19 patients. There is a need for more clinical trial studies for approval of these results.

The aim of this study was to empirically examine how much traditional attributes and green attributes characterize products within design-oriented firms. Further, we explored how these attributes relate to the perceived level of innovation of the firms.

An exploratory research was carried out in 86 Italian manufacturing companies that are members of the Industrial Design Association. Using the questionnaire method, the entrepreneurs’ perceptions have been analyzed. Data have been treated with hierarchical cluster analysis.

The analysis shows that environmental sustainability is the least important attribute of a design product and four clusters of highly design-oriented firms differ by design-product attributes. Further, the least green firms are also the least innovative in terms of incremental and general innovation.

The small size of the sample and the provenance of firms from a single country imply limited generalizability, and further research on the topic is recommended.

Design-driven innovation based on traditional design attributes provides many competitive advantages to firms. However, given the growing concern about environmental challenges, investing in green attributes in design products allows for remaining competitive and more effective in innovation.

This study, for the first time, reveals the heterogeneity among design-oriented firms, particularly regarding the presence and assortment of traditional design attributes, as well as the incorporation of environmentally friendly attributes in their products. Moreover, the study uncovers the relationship between varying levels of green attributes in the offerings and the perception of the firm’s innovativeness.