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Induction heating as an energy source is a novel, recent method in extrusion-based metal additive manufacturing. The purpose of this paper is to develop an optimized coil for extrusion-based metal wire additive manufacturing. The optimized coil is so designed that uniform temperature distribution can be achieved in the extruder, achieving uniform material deposition in a semi-solid state, which is required for additive manufacturing.

Coil shape optimization is achieved by using arrangement of coil turns as a control variable in the form optimization process, and the objective function is to minimize the gradient in the distribution of the magnetic field to achieve uniform heating in the extruder for maintaining consistent solid and liquid fraction during material deposition. A combination of numerical solutions and geometrical optimization has been used for this study.

Experimental and simulation results reveal that the optimized induction coil produced a more uniform axial temperature distribution in the extruder, which is suitable for maintaining a uniform solid-to-liquid fraction ratio during material deposition.

The author has investigated the use of optimized-shaped induction coils in extrusion-based additive manufacturing. The optimized coil can achieve a more uniform temperature distribution in the extruder in comparison to the standard helical coil used in the existing process, which means optimized coil achieves a more uniform solid-to-liquid ratio during printing in comparison to existing standard coil shapes used for heating extruders and fulfils the requirement of additive manufacturing.

The failure rate of international construction joint venture (ICJV) projects has been noted to be high in developing countries due to the complexity and risky nature of construction projects in the international market. The purpose of this study is to identify and evaluate the risks facing ICJV projects in Ghana.

A risk register was developed through a comprehensive literature review. The identified risks were then used in a questionnaire survey involving local and foreign partners in ICJV projects in Ghana.

From a total of 74 risks identified, categorized into country-level risks, market-level risks and project-level risks, the “top ten” risks found to be the most critical risks facing ICJV projects in Ghana include unstable currency exchange rates, inflation, design changes, high-interest rate, budget overrun, cash flow problems of the client, economy fluctuation, difficulty in obtaining approval of projects from host government authorities/bureaucracy, potential financial distress of JV partner and bribery and corruption.

This study provides a comprehensive list of risks ICJV partners are likely to encounter on their projects in developing countries. Furthermore, this study improves on one of the major limitations of previous ICJV studies by collecting data from both partners of the ICJV, appropriate for cross-cultural examination and comparison.

As an important form of the e-commerce industry, online group buying is under the spotlight from with two sides: cheaper price but longer waiting time. The purpose of this paper is to adequately investigate the interaction between saving and waiting time of group buying comprehensively.

To fill the research gap, the authors elaborate a dual-channel supply chain (SC) with regular retail (individual buying) and group-buying channel, and formulate the demand based on the consumer utility with the positive effect of saving money and the negative effect of wasting time.

The authors find that power structure only changes the optimal prices, instead of the waiting time. The selling price mainly influences consumer demands, instead of the price discount of group buying. The SC profits are only positive to the channel preference, and it is the decisive parameter of consumers' choice. The price sensitivity lays a more remarkable impact on the SC compared to the time sensitivity. Above all, the price is the main factor of group buying, instead of time.

These results underscore the improvement for the dual-channel SC of group buying, providing managerial insights for the group-buying industry.

This paper divides the dyadic supply chain into three power structures according to the relative channel power of the supply chain members and consequently examines the optimal supply chain pricing decisions when both suppliers and retailers are concerned with fairness issues.

Three models are constructed, namely the Stackelberg game model with the supplier as the leader, the Nash game model with the balance of power and another Stackelberg game model with the retailer as the leader. The equilibrium solutions are solved, and their results are analyzed.

The retail price of a product increases with an increase in the fairness concerns of the leader in a supply chain in which the supplier or retailer is the leader, while the fairness concerns of the member with less channel power have no effect on the retail price. In a power-balanced supply chain, both suppliers and retailers increase their retail prices as their fairness concerns increase. The relative size of the members’ fairness concerns affects member profits and total supply chain profits.

The main contributions are as follows: First, this paper proposes a new approach to studying supply chain pricing strategy, considering fairness concerns and power structure. Secondly, three game models are constructed. The Nash equilibrium solution is introduced to study the fairness of supply chain participants in pricing decisions and overall supply chain profitability. Finally, the supply chain management theory is expanded by this study on pricing decisions and supply chain performance.

This study aims to develop a polymer cement-based waterproof coating with self-healing capability to efficiently and intelligently solve the building leakage caused by cracking of waterproof materials, along with excellent durability to prolong its service life.

Ion chelators are introduced into the composite system based on ethylene vinyl acetate copolymer emulsion and ordinary Portland cement to prepare self-healing polymer cement-based waterproof coating. Hydration, microstructure, wettability, mechanical properties, durability, self-healing performance and self-healing products of polymer cement-based waterproof coating with ion chelator are investigated systematically. Meanwhile, the chemical composition of self-healing products in the crack was examined.

The results showed that ion chelators could motivate the hydration of C₂S and C₃S, as well as the formation of hydration products (C-S-H gel) of the waterproof coating to improve its compactness. Compared with the control group, the waterproof coating with ion chelator had more excellent water resistance, alkali resistance, thermal and UV aging resistance. When the dosage of ion chelator was 2%, after 28 days of curing, cracks with a width of 0.29 mm in waterproof coating could fully heal and cracks with a width of 0.50 mm could achieve a self-healing efficiency of 72%. Furthermore, the results reveal that the self-healing product in the crack was calcite crystalline CaCO₃.

A novel ion chelator was introduced into the composite coating system to endow it with excellent self-healing ability to prolong its service life. It has huge application potential in the field of building waterproofing.

This paper aims to specifically analyze the interrelationships of employee political skill and personal reputation with both workplace and non-workplace outcomes. The study further focuses on performance and career development as workplace outcomes and entrepreneurial intentions as a non-workplace outcome, while analyzing employee political skill and personal reputation.

The study uses a survey method, where multi-source data were collected in a time-lagged fashion from the employees working in the textile sector in an under-researched emerging economy setting of Pakistan.

The findings establish that political skill is a significant predictor of employee job performance, career development and entrepreneurial intentions. Moreover, the mediating role of personal reputation was confirmed for the proposed relationships. Hence, the findings highlight the contributory role of personal reputation in the enhancement of workplace and non-workplace outcomes, such as entrepreneurial intentions linked to political skill.

Despite some limitations, this paper offers theoretical implications both for political skill and indirect reciprocity literature. A vital theoretical contribution is extended by studying the mediating role of personal reputation in the main relationships analyzed in this paper. The scope of indirect reciprocity is expanded by identifying personal reputation as a vital mechanism for indirect reciprocity.

Organizations should focus on developing political skill amongst their employees, as these skills are salient for amassing a favorable reputation, that eventually leads to performance, career growth and development of entrepreneurial intentions. Organizations should put in place careful selection and coaching and mentoring programs that equip employees with such skills that eventually lead toward the alignment of employees’ personal goals and organizational goals. Employees, then, could focus on priming both organizational and personal goals.

This paper is one of the pioneering studies that specifically link employee political skill with job performance, career development and entrepreneurial intentions, especially in the relatively volatile and under-researched context of Pakistan. Another novelty of this research is the investigation of personal reputation as a psychological mechanism underlying the primary relationships proposed in this research.

A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution.

A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI.

Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality.

This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

This paper aims to unveil the greenwashing intention of green bonds issuing in Chinese enterprises through the lens of stock pricing efficiency.

Drawing on data of Chinese listed companies during 2012–2021, this study uses a difference-in-differences method to study how and through what mechanisms issuing green bonds impacts stock pricing efficiency.

Issuing green bonds lowers stock pricing efficiency, verifying the greenwashing intention of green bonds in China. Potential mechanisms underlie the increased investor attention and sentiment resulting from the information disclosures about corporate green and low-carbon development. This greenwashing issue is more pronounced in firms facing lower financing constraints, having stronger relations with the government, and located in highly marketized regions. In the context of uncertainty surrounding economic policies, especially trade policies, issuing green bonds can signal a weakening of the greenwashing effect.

The quality of information disclosure should be emphasized to ensure a substantive commitment to environmental responsibility signaled by green bond issuance, thereby mitigating greenwashing concerns.

Regulators and standard-setters should improve the issuance system for green bonds and promote the sustainable development of the green bond market through formulating unified certification criteria for green bonds and implementing a stringently periodic reporting system.

First, to the best of the authors’ knowledge, it is the first study to draw on the quality of information disclosure and the perspective of stock pricing efficiency to identify whether firms issuing green bonds engage in greenwashing. Second, the study uncovers the black-box underlying this greenwashing issue through investor attention and sentiment and examines further the moderating role of economic policy uncertainties.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.