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In the servicization business model, a service-oriented manufacturer sells the service derived from its products. Because of the special compensation method, a service-oriented manufacturer is more likely to be underfunded. A Stackelberg game is formulated to investigate the interaction among a bank, a manufacturer, and an operator, in which two financing strategies are considered: bank financing and guaranteed (internal) financing. The difference between these two strategies is who bears the bankruptcy risk of the manufacturer. With bank financing, the bank bears the risk and determines the interest rate, while under guaranteed financing, the operator sets a guaranteed financing interest rate. We find that under bank financing, the low operating efficiency of the manufacturer increases the bank's share of the supply chain benefits. In particular, the service-oriented manufacturer can rarely be financed if the bankruptcy risk is high. However, under guaranteed financing, the operator may, interestingly, even subsidise a manufacturer with high operating efficiency. In this situation, a high bankruptcy risk could incentivize the manufacturer to improve its operating efficiency for the sake of the subsidy. Practically, guaranteed financing could coordinate the supply chain through interest rate adjustments or subsidies when facing different risk levels, which could improve both firms' benefits. [ABSTRACT FROM AUTHOR]

This paper proposes a service-oriented manufacturing strategy in a two-echelon supply chain with random demand. When there is no inventory for the retailer to meet demand, customers can choose to order products through the retailer and products will be delivered to them by the manufacturer directly in the promised time, and we call this delivery service in service-oriented manufacturing. We employ a Stackelberg game-theoretic model to analyse the procurement quantity and delivery time decisions by the manufacturer as the leader and the retailer as the follower. Using the performance of the pure-manufacturing strategy as a benchmark, our main results follow. First, the equilibrium strategies of the two players are obtained. Clear decision rules are also given. Second, delivery service in service-oriented manufacturing can be an effective way to reduce the holding cost of the retailer. Third, we describe the customer loss caused by waiting and find how the manufacturer influences procurement quantity of the retailer through the decision of delivery time. Finally, delivery service in service-oriented manufacturing cannot always improve the profit of the manufacturer and the retailer. We give guidance for managers to provide it. [ABSTRACT FROM AUTHOR]

This paper explores the optimal homing policy of a manufacturer who sells products through two competing platforms: a traditional online platform and a social commerce platform. The social platform can choose to operate with reselling or agency selling format. Through analysis, we first find that the manufacturer's optimal decision regarding whether to single- or multi-home and the social platform's optimal decision regarding whether to adopt reselling or agency selling format depend mainly on the intensity of the downstream competition and the platforms' market sizes. Specifically, the manufacturer prefers single-homing if the competition intensity is relatively low and the traditional platform's market size is relatively large. When the competition intensity increases (decreases), the agency selling (reselling) format is always the social platform's preferred choice. Next, we find that the manufacturer is less likely to choose multi-homing (single-homing) and the social platform is more likely to select agency selling (reselling) format when the traditional platform serves as a marketplace rather than a reseller. Finally, numerical studies show that the manufacturer's and the platforms' preferences for selling modes are always misaligned. However, an all-win situation is achieved with the pure agency selling mode when the competition intensity is relatively high. [ABSTRACT FROM AUTHOR]

As a manufacturing power in the era of Industry 4.0, the Chinese traditional manufacturing industry urgently needs innovation and upgrading. In this process, the pressure on the traditional manufacturing industry is mainly financial shortages. The government can act as a Booster to add power to the upgrading by providing financial support. We build a three-tier game model consisting of Raw Material Suppliers, a Traditional Manufacturer, and an Original Equipment Manufacturer to explore the upgrading conditions and construct three settings: Agency, Consignment, and Design. We find that the government subsidy can serve as an effective way to ease enterprises' financial burden and improve the innovation level, which is more evident when the traditional manufacturer innovates. In addition, when the market competition and the government subsidy are both at a moderate level, the combined effect of the two factors is positive, and the condition is the best to upgrade. Encouragingly, the social welfare under Design will be the highest when the government subsidy is slightly great. Finally, excessive subsidy hinders upgrading and aggravates market competition, even if the traditional manufacturer enjoys exorbitant profits. HIGHLIGHTS The upgrading on the manufacturing industry in the era of Industry 4.0 The right of product design in supply chain models The cross-influence of the government subsidy and market competition on industrial upgrading is introduced The conditions to help upgrade the manufacturing industry are given in the era of Industry 4.0 [ABSTRACT FROM AUTHOR]

Compared to the traditional channel, where a retailer bears the inventory risk, the drop-shipping channel operates with a distinct approach: the retailer avoids stocking products while the manufacturer directly handles stocking and shipping to consumers. Due to the different inventory risk allocations, the two channels have different product qualities and profits for the manufacturer and retailer. In this study, we investigate product quality decision of the manufacturer and delve into the impact of product quality on the manufacturer's and retailer's profitability. First, we find that product quality can be weakly higher in the drop-shipping channel than that in the traditional channel. This is because the drop-shipping channel allows the manufacturer who undertakes demand uncertainty to charge a higher wholesale price, resulting in a higher product quality. Second, our study reveals that the traditional channel can concurrently yield higher profits for the manufacturer and retailer when product quality is considered, which is in contrast to the previous works. Third, in the traditional channel, as demand uncertainty rises, the retailer's production quantity increases, while the manufacturer's product quality decreases. Finally, our results indicate that the product quality is more sensitive to the shipping cost when demand uncertainty is low. [ABSTRACT FROM AUTHOR]

We consider a manufacturer and an e-platform where the manufacturer sells products through offline and e-platform channels under the cap-and-trade scheme. The interaction between the two channels produces the cross-channel effect (CCE). This manufacturer cooperates with the e-platform in the agency or reseller mode. In addition, the platform shares its observed data with the manufacturer and the blockchain can achieve traceability and high transparency of these data. We formulate a Stackelberg game to derive the following results: In the agency mode, the optimal service level is independent of (decreases with) CCE without (with) blockchain. CCE positively affects the optimal service level in the reseller mode and the optimal service level has no impact on (increases with) the cap in the agency (reseller) mode. Second, when the platform-enabled power is high (low), the platform is (not) willing to adopt blockchain. Third, coordination of the manufacturer and platform only can be achieved in the agency mode when CCE is low with blockchain. The reseller mode can (cannot) achieve coordination of the two firms with (without) blockchain. We also consider the cases where the manufacturer serves as the leader and the omni-channel strategy is adopted to check the robustness of the coordination results. [ABSTRACT FROM AUTHOR]

This paper constitutes a comparative assessment of the impact of robots on local labor markets across eight European countries. Doing so, we find that robots generally reduce employment in the manufacturing sector, while their impacts on total employment are more ambiguous. Though local markets experienced significant employment losses in Italy, Norway, and the United Kingdom, we find no statistically significant impact of robots on employment in Germany, Sweden, Denmark, Finland, and Spain. Job losses were seemingly offset by employment gains in other sectors of the economy. We explore two mechanisms that might explain these patterns: differences in investment in complementary job-creating technologies and robot-induced reshoring. Our analysis provides some support for both mechanisms in elucidating the differential impacts of robots on jobs across space. [ABSTRACT FROM AUTHOR]

In modern manufacturing and service industries, urgent orders and service tasks are common, and the speed of handling such urgent tasks is an important indicator of production and service efficiency. In this study, we consider scheduling jobs on two parallel machines with the random arrival of an emergency job. The objective is to minimise the makespan, subject to a given maximum waiting time of the emergency job. We first show that the worst-case ratio of the existing algorithm LPT $ _l $ l -SPT $ _{m-l} $ m − l is at least 3/2 when m = 2. We then analyse some properties of the optimal schedule and derive lower bounds on the optimal makespan. Finally, we present an improved approximation algorithm with a tight worst-case ratio of 4/3. We also provide numerical results showing that our proposed algorithm outperforms algorithm LPT $ _l $ l -SPT $ _{m-l} $ m − l . [ABSTRACT FROM AUTHOR]

The outbreak of the Covid-19 pandemic led to restrictions in production worldwide. Numerous firms were affected and unable to keep up production due to lockdowns. In disruptive events like this, the resilience of the production system is of central importance, as the survivability of the entire firm depends on it. In this context, the literature argues that cutting-edge technologies, such as Artificial Intelligence (AI), raise the proactive and reactive capabilities of firms, enabling them to better resist and recover from disruptive events and thus, show a higher resilience. This paper takes up this topic and observes the Covid-19 pandemic with the aim to analyse whether a firm's AI-readiness had an impact on its production resilience during the spring 2020 lockdown in Germany. For this purpose, we combine two large-scale surveys containing data from 237 manufacturers in Germany and test hypotheses based on quantitative analyses. Our results show that firms could indeed benefit from AI-enabled production during the lockdown. However, it is also clear that manufacturers have to exceed a certain AI threshold to significantly increase their resilient capabilities and realise positive effects. Our findings not only hold implications for research, but also provide recommendations for the resilience management of manufacturers. [ABSTRACT FROM AUTHOR]

This paper revisits the ongoing discussion on the concept of industrial relatedness by applying it to manufacturing industries in urban areas. The analysis uses a sample of firms operating in the Brussels Capital Region area and observed over the period 2009–2015. Based on a two-step quantile regression, results show that industrial relatedness is the agglomeration force that mostly sustains the performance of urban manufacturing, whereas this is not the case for other types of agglomeration externalities. Moreover, among the measures of industrial relatedness, the input–output relationship matters more than product similarity in the perspective of a relocation of manufacturing firms in urban areas. [ABSTRACT FROM AUTHOR]

Energy efficiency has become a major concern for manufacturing systems, due to industry being the largest user of scarce, finite energy sources, and also to recent events which have pushed energy prices to alarming levels. In the present Industry 4.0 context, Reconfigurable Manufacturing Systems (RMS) are therefore one of the most promising manufacturing paradigm. In this paper, we investigate the suitability of one of the most common types of RMS, the Parallel-Serial manufacturing line with Crossover, to help minimise the peak of the electric power consumption. More specifically, the balancing of such a production line is studied, so as to integrate power peak minimisation from the design stage. Thus, we define the Parallel-Serial-with-Crossover Assembly Line Balancing Problem with Power Peak Minimization, a new combinatorial NP-hard problem. We also propose a suitable time-indexed Integer Linear Program that integrates balancing and scheduling decisions and a matheuristic algorithm designed to tackle large-size instances. Both approaches are tested on a wide set of instances. The computational results show that relevant power peak reductions can be achieved (33% on average), opening up promising perspectives from both algorithmic and managerial viewpoints. [ABSTRACT FROM AUTHOR]

Rapid advances in new-generation information technologies have been the main driving force for the transformation of manufacturing enterprises in Industry 4.0. Digital twin (DT), as a key technology to promote intelligent manufacturing, has shown great potential for manufacturing enterprises to create an industrial intelligence-driven production equipment through in-depth integration of cyber-physical systems. However, the lack of a systematic effective DT modelling method with a supporting evaluation metric is the most important factor restricting the application of DT in manufacturing enterprises. To bridge the gap, this paper proposes a novel multi-level modelling and fidelity evaluation (MLM&FE) method of DT for creating smart production equipment in manufacturing enterprises, which could help enterprises establish an industrial intelligence-driven production environment to quickly respond to changes in the customised global market, thus greatly improving competitiveness of the enterprises. Specifically, this paper firstly designs a reference framework for DT-enhanced smart production equipment, on which an MLM&FE architecture is proposed. Then, key implementation methodologies and tools for MLM&FE are introduced from the perspective of data space modelling, virtual space modelling, knowledge space modelling, model integration and evaluation. Finally, the developed smart production equipment prototype demonstrates the feasibility and effectiveness of DT MLM&FE. [ABSTRACT FROM AUTHOR]

Yes. We show that aggregate stock returns predict aggregate U.S. employment, despite the industrial composition of publicly traded firms differing markedly from that of all firms, and the representativeness of public firms declining over time. We also show that appropriately reweighted stock returns predict industry and local labor market outcomes. We find the strongest evidence of an alignment of interests between shareholders and workers in the manufacturing sector, despite its declining labor share of output. Our findings suggest that at quarterly frequencies, product demand shocks are more important drivers of industry- and city-level stock returns than technology shocks. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic's impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). This article examines extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research. [ABSTRACT FROM AUTHOR]

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Consumers' perception of product value when purchasing is a critical issue relative to online platform commerce. This is especially true when the brand manufacturer authorises only a third-party reseller to sell through the platform, a practice that may provide opportunities to counterfeiters. To address this issue, we establish a theoretical model in which one brand manufacturer wholesales its products to a third-party reseller who then sells through an online platform. The platform acts as a marketplace, while multiple counterfeiters also exist on the platform, which may deceive consumers. In particular, we consider that the manufacturer can encroach with a direct channel and that the platform can adopt blockchain technology to help consumers identify authenticity. The results show that the platform could induce the brand manufacturer to encroach by deploying blockchain technology. Furthermore, an interesting result indicates that although either manufacturer encroachment or blockchain technology used alone can effectively boycott counterfeits, the coexistence of two strategies can raise the demand for counterfeit products. Finally, we find that when the brand manufacturer encroaches on the platform and the platform adopts blockchain technology, the brand manufacturer, platform, reseller and social welfare can achieve Pareto improvement, while the consumer surplus may be worse off. [ABSTRACT FROM AUTHOR]

For one-of-a-kind production (OKP) manufacturers adopting an engineer-to-order or make-to-order marketing strategy, it is very important to set an appropriate due date. We design an incentive-compatibility due-date quotation procedure to help OKP manufacturers obtain the rational due-date quotation from OKP customers. Based on the rational due-date quotation decision-making, the performance of an OKP shop floor controlled by load-based pull systems is evaluated in simulation. Our findings show that if the collaboration of due-date quotations and load-based pull control is effective, the order profit of OKP manufacturers will not be reduced when the delivery delay occurs. This study can provide more insights on order quotation decision-making and pull production control for OKP manufacturers. [ABSTRACT FROM AUTHOR]

Supply chain viability (SCV) is associated with systematic and dynamic approaches to responding to COVID-19 disruptions. The supply chain has been disturbed due to the recurrent nature of the pandemic. In the post-pandemic era, large and small- and medium-sized manufacturers have both advantages and disadvantages, complementing each other. This study proposes an agent-based model to simulate the viable situation of heterogeneous supply systems by considering three behavioural rules (i.e. cooperation establishment, win-win cooperation, and cooperation priority). The results demonstrate that the viability will be improved if large manufacturers cooperate closely with small- and medium-sized manufacturers. The viability is also associated with two adjustment parameters of production capacity, indicating that large manufacturers need to become more scalable, flexible, and adaptable to survive a rapidly changing environment. In addition, when the cooperation is more widely-connected, the viability will be higher. When facing severe fluctuations, large and small- and medium-sized manufacturers can cooperate, acting as a 'sponge system' to flatten the fluctuations. Finally, the simulation results of an empirical network also support this conclusion. Therefore, we suggest that a viable supply chain design should consider integrating supply resources to improve the overall viability of the supply system. [ABSTRACT FROM AUTHOR]

We examine the manufacturer's encroachment strategy in the supply chain in the presence of the retailer's in-store service. The manufacturer has the option of encroachment with a direct channel, and the retailer has the option of providing in-store service. If the retailer decides to offer service, it sets the service level. We show that in the presence of in-store service, the manufacturer is less likely to encroach on the retail market than in the absence of in-store service. The retailer always prefers to provide in-store service. If the manufacturer decides to encroach, it will strategically use its direct channel with no sales as a threat to the retailer, independent of whether or not the retailer provides in-store service. The retailer can be better off with manufacturer encroachment, but it can be worse off when consumer sensitivity to in-store service is very low. We show that the retailer can strategically employ in-store service to deter the manufacturer's encroachment when the consumer sensitivity to in-store service is sufficiently high. [ABSTRACT FROM AUTHOR]

When does pay dispersion elicit positive or negative employee attitudes? A review of the pay dispersion literature indicates a controversy around this vital question and suggests that numerous contingency factors moderate the effects of pay dispersion. In an empirical study of four Finnish companies consisting of 141 work units, we examine contingencies in attitudinal reactions to job‐based pay dispersion among blue‐collar workers. Based on archival pay data matched with employee survey responses (n = 536), we find that perceptions of pay basis legitimacy, task interdependence, and an individual's pay standing within the work unit explain the strength and direction of the relation between job‐based pay dispersion and employee attitudes (i.e., work engagement and organizational commitment). Our findings have implications for the design of pay systems and contribute to a better appreciation of the complexities underlying employee attitudinal responses to pay dispersion. [ABSTRACT FROM AUTHOR]

Contributing to the literature on positive effects of overqualification, this research examines when and why perceived overqualification predicts affiliative and proactive performance at work. Integrating optimal distinctiveness theory with self‐construal theory, we propose that depending on the nature of an employee's self‐construal (i.e., independent, or interdependent), perceived overqualification will be associated with two opposing motivational processes—namely, differentiation and assimilation. We expect perceived overqualification to have a positive relationship with a motive for assimilation when an employee has a strong interdependent self‐construal. Conversely, we expect perceived overqualification to have a positive relationship with a motive for differentiation when an employee has a strong independent self‐construal. We further argue that assimilation‐seeking and differentiation‐seeking motives will be positively related to affiliative and proactive performance, respectively. We conducted two multi‐waved and multisourced studies to test our hypotheses. In a pilot study (N = 249), we first tested our moderation hypothesis. In our main study (N = 496), we tested our overall moderated mediation model. Results from both studies reveal that perceived overqualification can trigger a need for differentiation or assimilation in employees depending on the nature of their self‐construal. The differentiation‐seeking motive was positively related to proactive performance, while the assimilation‐seeking motive was positively related to affiliative performance. Our findings advance overqualification and motivation literatures and provide insights into talent acquisition and management. [ABSTRACT FROM AUTHOR]

After decades, dialogues on human resource management (HRM), intellectual capital (IC), and ambidexterity still continue, mirroring that the role of ambidextrous capability in translating the impact of HRM into superior performance remains unclarified. At this juncture, the current study proposes a novel theoretical framework to extend research on the relationship between IC‐enhancing HR practices and innovation. It is done sophisticatedly by examining how firm exploitative and exploratory capabilities mediate the relationship between different combinations of HR configurations and firm innovation. To this end, we designed rigorous time‐lagged research with three waves of data collection from the Iranian healthcare sector. Our analyses revealed that firm explorative and exploitative capabilities significantly mediate the relationship between human, social, and organizational capital‐enhancing HR configurations and firm innovation. More conspicuously, by unraveling interaction patterns among distinct HR configurations, our study revealed the intricacies of the functioning of IC‐enhancing HR practices in fueling firm ambidexterity. Hence, our study offers design options to navigate through exploitation and exploration in light of the firm's core innovation strategy. We discuss the theoretical and practical implications of our findings and suggest future research avenues. [ABSTRACT FROM AUTHOR]

Human-centricity is the core value behind the evolution of manufacturing towards Industry 5.0. Nevertheless, there is a lack of architecture that considers safety, trustworthiness, and human-centricity at its core. Therefore, we propose an architecture that integrates Artificial Intelligence (Active Learning, Forecasting, Explainable Artificial Intelligence), simulated reality, decision-making, and users' feedback, focussing on synergies between humans and machines. Furthermore, we align the proposed architecture with the Big Data Value Association Reference Architecture Model. Finally, we validate it on three use cases from real-world case studies. [ABSTRACT FROM AUTHOR]

Changing customer requirements and turbulent markets require suitably adapted capabilities to proactively cope with rapid changes. Agile manufacturing emerged in the late 1990s as a competitive concept to respond to these business challenges. While several seminal research works address agility in terms of concept definition, drivers and strategic capabilities, there is a lack of implementation frameworks of agile manufacturing. The current paper is concerned with the question of how to improve the agility of manufacturing companies. To address this question, a framework is iteratively developed with the aim of supporting decision makers in planning and implementing agility improvement projects. To this end, Design Science Research (DSR) methodology is used in conjunction with CIMO-logic (Context, Intervention, Mechanism, Outcome). The iterative development of the framework relies heavily on insights from case studies and from practitioners in the broad manufacturing sector. The paper provides evidence of the validity of the framework as well as outlining further research perspectives. [ABSTRACT FROM AUTHOR]

Industry 4.0 concepts make it possible to rethink human resources allocation, even for more traditional environments like metal machining. While parts machining on Computer Numerical Control (CNC) machines is automated, some manual tasks must still be executed by operators. The current approach is typically that operators are statically allocated to one or many machines. This causes avoidable bottlenecks. We propose an optimisation model to dynamically assign tasks to the operators with the objective of minimising production delays. Three different scenarios are compared; one representing the current widely used static allocation method and two others that allow more flexibility in the operators' allocation. The dynamic task assignment problem is solved using a constraint programming model. The model was applied to a case study from a high-precision metal manufacturing job shop. Experimental results show that switching from a static allocation to a dynamic one reduces by 76% the average production delays caused by human operators. Supposing more versatile operators under the dynamic allocation leads to further improvements. [ABSTRACT FROM AUTHOR]

Industry 4.0 aims to establish highly flexible production, enabling effective and efficient mass customisation of products. Modelling techniques and simulation of production processes are among the core techniques of the manufacturing industry that facilitate flexibility and automation of a shop floor in the era of Industry 4.0. In this paper, we present an approach to support production process modelling and process model management. The approach is based on Model-Driven (MD) principles and comprises a Domain-Specific Modelling Language (DSML) named Multi-Level Production Process Modelling Language (MultiProLan). MultiProLan uses a set of concepts to specify production process models suitable for automatic instruction generation and execution of the instructions in a simulation or on a shop floor. By using MultiProLan, process designers may create process models independent of the specific production system. Such process models can either be automatically enriched by matching and scheduling algorithms or manually enriched by a process designer via MultiProLan's modelling tool. In this paper, we also present an application of our approach in the assembly industry to showcase its dynamic resource management, generation of production documentation, error handling and process monitoring. [ABSTRACT FROM AUTHOR]

Customer demands force manufacturing companies to offer individualised products to remain competitive. This results in a demand for flexibility and adaptability in product development and production, which causes a rise in complexity. Simultaneously, manufacturers strive to further automatise production and assembly lines to increase cost efficiency and optimise output. This leads to a conflict of interest between two different approaches, 'streamlined and cost-efficient' or 'individualised and costly'. Software-Defined Manufacturing (SDM) is a new approach that seeks to reconcile these diametrical goals by increasing the adaptability of automated manufacturing. This is achieved by virtualising key functionalities of production machines, which permit the configuration of system functionality via software. With current production equipment, this is difficult, because it was designed for a specific process and because there is no meaningful separation between the executing physical part of the machine and the controlling software. This article presents a new method for the development of SDM-ready production machines and processes. The application of the method on a production use-case demonstrates its usefulness in the improvement of existing production facilities and processes. It further addresses the wider trend of Software-Defined Anything (SDx) and outlines the role SDM could play on the pathway towards autonomous manufacturing. [ABSTRACT FROM AUTHOR]

There is a powerful global trend toward deeper integration of digital twins into modern life driven by Industry 4.0 and 5.0. Defense, agriculture, engineering, manufacturing, and urban planning sectors have thoroughly incorporated digital twins to great benefit across their respective product lifecycles. Despite clear benefits, a digital twin framework for health and medical sectors is yet to emerge. This paper proposes a digital twin framework for precision neuromusculoskeletal health care. We build upon the International Standards Organization framework for digital twins for manufacturing by presenting best available computational models within a digital twin framework for clinical application. We map a use case for modeling Achilles tendon mechanobiology, highlighting how current modeling practices align with our proposed digital twin framework. Similarly, we map a use case for advanced neurorehabilitation technology, highlighting the role of a digital twin in control of systems where human and machine are interfaced. Future work must now focus on creating an informatic representation to govern how digital data are passed to, from, and within the digital twin, as well as specific standards to declare which measurement systems and modeling methods are acceptable to move toward widespread use of the digital twin framework for precision neuromusculoskeletal health care. [ABSTRACT FROM AUTHOR]

Strengthening carbon regulations and competitive pressures are forcing supply chains to provide environmental (e-) products to replace traditional (t-) products. However, cap-and-trade policy allows manufacturers, the main carbon emission emitters, to trade their emission permits freely. Considering manufacturers' power and key role in producing and carbon trading, we develop a duopoly model consisting of two competing manufacturers. Despite asymmetrical carbon emission reduction efficiencies, the two manufacturers can independently and simultaneously decide their respective t-/e-products outputs, emission reduction levels, and permits trade quotas. The unique Nash equilibrium is derived with the overall cap. We find that the low-cost manufacturer uses its cost advantage to invest more in emission reduction, then sells the excess emission permits to its rival, but makes its rival more competitive in product market. Interestingly, our results show that cap-and-trade policy triggers an industry collusion in which manufacturers reduce competition and improve the power and profits by reducing overall output and adopting differentiated product strategy. Furthermore, the cost advantage and high product substitution can accelerate low-cost manufacturer's transformation but hinder high-cost manufacturers. The impacts of cap-and-trade policy on consumer surplus and social welfare are also discussed to provide guidance for policy makers. [ABSTRACT FROM AUTHOR]

This study estimates the impact of non-tariff measures (NTMs) on the hazard rate of trade relationships. A random-effects probit analysis shows that imposing NTMs moderately increases hazard rate but that effects in manufacturing industries vary depending on the nature of NTMs. Non-quality related NTMs lead to a higher hazard rate, while quality-related measures significantly lengthen trade relationships. [ABSTRACT FROM AUTHOR]

The Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) legislation in Europe has limited the use of certain materials in the manufacturing of tattoo inks; in particular, Pigment Blue 15:3 and Pigment Green 7 have been banned for the use in tattoo inks and permanent makeups and all labels must include an accurate list of ingredients. This study analyzed green and blue inks from five different manufacturers distributed to the European market, all of which claim to be REACH compliant. Nine out of ten inks analyzed were found to not be compliant and four contained banned material. The polymorph of Pigment Blue 15 found in four inks was unable to be determined. The majority of inks showed labeling inaccuracies, including the addition of unlisted poly(ethylene glycol) and propylene glycol. This study highlights issues around REACH compliance of tattoo inks on the European market and the need for manufacturing protocols to ensure accurate labeling. [ABSTRACT FROM AUTHOR]

In 2016, the Spanish Mission at Dra Abu el-Naga (hereafter SMDAN), directed by José M. Galán, found eight cartonnage mummy-cases. They were torn into pieces and discovered in the largest shaft and burial chamber of a group of funerary and commemorative structures that are located to the south-west of the open courtyard of the tomb-chapel belonging to Djehuty (TT 11). Built during the late 17th or early 18th dynasties, the shaft and chamber were thoroughly plundered and repeatedly reused over several centuries, especially during the Third Intermediate Period. One of the cartonnages, SMDAN 1353, made for Paysetjenfy, has been selected for a comprehensive analysis of its decoration, including its state of preservation, technique of execution and its textual and iconographic content. A combined study of the archaeological context and the materiality of this artefact, with a search for parallels for its decoration and an investigation into the genealogical and prosopographic information concerning its owner are undertaken. This type of research will help to contextualise this cartonnage within the Theban manufacturing industry of cartonnage cases and the complex social structure of families bearing the highest ranks in the priesthood of Amun during the 22nd dynasty. [ABSTRACT FROM AUTHOR]

Achieving sustainability performance seems to increasingly occupy the strategic agendas of organisations. Are organisations investing in their strategic agendas in Environmental, Social and Economic Sustainability? The research aims to analyze the innovative, dynamic capabilities effect on Sustainability performance (Environmental, Social and Economic). The hypothesis adopted is that sensing, seising and transforming favour Sustainability performance over time. We have used a longitudinal multiple linear regression analysis of Brazilian Innovation Research (BIR) data, for 16 years, a sample of 41 manufacturing sectors. The findings suggest that transforming favours environmental sustainability, sensing and seising favour economic sustainability and seising favours social sustainability. This study answers how and to what extent the micro foundations of dynamic capabilities affect sustainability performance in the three dimensions. [ABSTRACT FROM AUTHOR]

In light of economic, social and discursive changes, old-industrial towns and regions increasingly apply entrepreneurial strategies to actively shape discourses as part of place-making processes. Foundational narratives play an important role in this regard. They are used by agents to foster cohesion in a local community, to legitimize and anchor their actions and goals and to make sense of complex development processes. Applying the methodology of Critical Narrative Analysis, the present study zooms in such processes of narrative building in Lauchhammer (Germany). Despite having experienced the decline of the most important parts of its industry, local actors still mobilize the industrial past in order to strengthen local identity and attract new businesses and manufacturers. Yet, the paper shows that different agents foreground different aspects of the industrial past and narratives may be contested. At the same time, local, regional and national development strategies are closely interlinked offering 'opportunity spaces' for local actors but raising also questions about a potential (de)legitimization of local narratives. [ABSTRACT FROM AUTHOR]

The adaptive versions of charting tools are well-established statistical monitoring techniques for detecting unknown changes in the process over a range of shifts. A re-weighted adaptive CUSUM mean (RACUSUM) charting scheme has been proposed in this study for monitoring the range of shifts. The proposed RACUSUM statistic estimates the unknown changes in the ongoing process using an EWMA statistic by plugging in an unbiased shift estimator and choosing a suitable smoothing constant according to the estimated shift to update the slack value of the CUSUM statistic. By employing Monte Carlo simulation using the zero- and steady-state processes, the proposal's run-length (RL) profiles have been calculated. The proposed RACUSUM chart shows more sensitive behavior under the shift delay process than in the case of zero-state. A comparative analysis between the proposal and competitors has been presented using average RL, extra quadratic loss (EQL), and the relative mean index (RMI) as metrics for 1-sided and 2-sided charting schemes. The robustness of the proposed 2-sided RACUSUM chart against non-normality has also been reported. The proposal's applicability has been demonstrated using two cases, one from the artificial and the other from a dataset of piston ring manufacturing industrial process. [Display omitted] • A new re-weighted adaptive CUSUM (RACUSUM) mean chart is designed to monitor shifts in the interval. • The proposal RACUSUM statistic estimates the unknown shift in the process mean. • The run-length (RL) profiles of the 1-sided and 2-sided proposed RACUSUM charts are evaluated using Monte Carlo simulation. • The extra quadratic loss (EQL) and relative mean index (RMI) metrics have been selected for the shifts in the interval. • The designed structure is applied to real piston ring industrial process data. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF (EO-PERF relationship). In particular, this study aims to explain the impact of KM on the relationship between the EO dimensions and PERF; dimensions are risk-taking (RT), innovativeness (IN) and proactiveness (PR). Design/methodology/approach: This study uses structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) methodologies to explore target relationships. The sample consists of 150 small furniture manufacturers operating in Poland (out of 1,480 in the population). Findings: The study findings show that KM partially mediates the IN–PERF relationship. Furthermore, fsQCA reveals that KM accompanied by IN is a core condition that leads to PERF. Moreover, the absence of KM (accompanied by the absence of RT and IN) leads to the absence of PERF. In addition, the results show that all the variables examined (RT, IN, PR and KM) positively impact PERF. Originality/value: This study explores the role of KM in the context of EO and its impact on PERF in the low-tech industry. The study uses simultaneously two methodologies that represent different approaches in the search for the expected relationships. The findings reveal that KM mediates the EO-PERF relationship. [ABSTRACT FROM AUTHOR]

Leader flexibility is considered necessary for leader effectiveness. However, there is limited research on antecedents of leader flexibility and its effect on leader effectiveness. This study, based on the leaderplex model, examines how multiple leader attributes influence leader effectiveness and subordinates' work behaviour and attitudes through leader behavioural complexity, an indicator of leader flexibility and ability to manage complexity. A total of 134 senior-level executives and their subordinates from 12 manufacturing organizations participated. Executives and their subordinates filled separate questionnaires. The executives provided data for their sociodemographics along with their cognitive complexity, cognitive flexibility, emotional intelligence, personality traits and subordinates' job performance. The subordinates provided data for their sociodemographics, commitment and work engagement, and leaders' behavioural complexity, overall effectiveness and performance. Results show leaders' cognitive flexibility, cognitive complexity, extraversion, emotional stability and agreeableness via behavioural complexity positively relate to leader effectiveness and subordinates' job performance. Except for the competitive mediation of extraversion, all other mediations were indirect. The indirect effects of cognitive flexibility and emotional stability on leader effectiveness and subordinates' job performance via behavioural complexity were medium. The other effects were low. Thus, this research contributes to the understanding of the association of different cognitive, social and personality attributes with leader effectiveness and subordinates' job behaviour and the role of behavioural complexity as a mediating mechanism in these relationships. [ABSTRACT FROM AUTHOR]

Grounding in the nexus of the relational capital theory and dynamic ambidexterity view, this study examines the effect of supplier collaboration on supply chain capabilities including flexibility and risk management using a sample of 195 manufacturers in China. It also assesses the antecedent role of the supply chain capabilities in building supply chain resilience and its resulting competitive advantage. This study employs path analyses using data collected from manufacturers. The findings of this study indicate the significant role of relational capital gained from supplier collaboration in building supply chain capabilities of flexibility and risk management capabilities, which are shown to lead to supply chain resilience. Competitive advantage also results from enhanced supply chain resilience. This study provides an integrated view of relational capital and ambidexterity for vulnerability mitigation and capabilities improvement, which offers implications to supply chain practitioners that maintaining a dynamic ambidexterity is critical to bolster supply chain resilience in the time of unexpected disruptive incidents. [ABSTRACT FROM AUTHOR]

In the current era of Industry 4.0 and Circular Economy, green logistics have become necessary for being sustainable. Adopting green logistics practices is a challenging task for the manufacturing industry, specifically in developing countries like India. In this study, we identified 16 barriers to implementing green logistics in the Indian manufacturing industry in reference to Industry 4.0 and circular economy. Data was collected from experts through a questionnaire-based survey. The decision-making trial and evaluation laboratory (DEMATEL) technique was applied to examine the degree of influence and interaction among the barriers. It has also helped in the classification of barriers into cause-and-effect categories. To validate the findings, a sensitivity analysis had also been carried out. The findings would help manufacturing organisations in developing strategies for implementing green logistics to achieve long-term sustainability. [ABSTRACT FROM AUTHOR]

The suboptimal level of vaccine research and development globally contributes to millions of people losing their lives to vaccine‐preventable diseases each year, the vast majority of whom live in developing countries. Vaccine manufacturers based in developing countries are increasingly participating in vaccine research and development to improve the availability of these life‐saving vaccine products. To understand the extent to which these emerging market vaccine manufacturers can contribute to global vaccine research and development, and thus improve health and societal outcomes, we examined the capabilities, priorities, and strategies of these organizations. We identified that emerging market manufacturers often engage in partnerships and solicit external support to alleviate the technical and financial hurdles associated with the complexity and cost of vaccine development. Focusing on unmet medical needs facilitates emerging market manufacturers' access to partners and external support and is critical in establishing a reputation in the global vaccine research and development ecosystem. [ABSTRACT FROM AUTHOR]

In this paper, a multi-objective hybrid flowshop scheduling problem (HFSP) with limited waiting time and machine capability constraints is addressed. Given its importance, the implementation of lot streaming division methodologies with the problem is investigated through a design of experiment (DoE) setting based on real data extracted from a leading tire manufacturer in Gebze, Turkey. By doing so, specific characteristics of the addressed HFSP can be further explored to provide insights into its complexity and suggest recommendations for improving the operational efficiency of such systems resembling it. Based on the problem specifications and constraints, a novel generic multi-objective optimization model with objectives including the makespan, the average flow time, and the total workload imbalance is formulated. Since the studied problem is NP-hard in the strong sense, several algorithms based on the non-dominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ) are proposed according to the division methodologies, i.e., consistent sublots and equal sublots. Since the main aim of this problem is to further analyze the implementation of lot streaming on the HFSP problem, the developed algorithms are compared with each other to gain remarkable insights into the problem. Four different comparison metrics are employed to assess the solution quality of the proposed algorithms in terms of intensification and diversification aspects. Computational results demonstrate that employing the consistent sublot methodology leads to significant improvements in all metrics compared to the equal sublot methodology. [ABSTRACT FROM AUTHOR]

Fuzzy front-end is the research frontier of manufacturing industry. This study investigates the relationship between market-oriented FFE activities and manufacturing startup growth performance by adopting an open innovative ancient Chinese Taoism Yin-Yang approach under this post-pandemic circumstance. This study also examines the moderating behavioral effect of Chinese Zen-originated CEO mindfulness between market-oriented FFE activities and manufacturing startup growth performance. Data for this study were gathered from 343 Chinese manufacturing startups' CEOs across different manufacturing industries, including both high-tech and conventional manufacturing industries. The collected data were analyzed by using structural equation modeling and Bootstrap method. The quantitative analysis results show that most market-oriented FFE activities have positive effects on manufacturing startup growth performance and the Chinese Zen-originated CEO mindfulness positively moderates the relationship between most FFE activities and startup growth performance. [ABSTRACT FROM AUTHOR]

The CLP mandates manufacturers and importers to classify substances and mixtures according to hazard criteria, with notifications submitted to the European Chemicals Agency (ECHA). Substances meeting hazard criteria must be appropriately labelled and packaged to communicate hazards effectively. The CLP establishes hazard classification criteria but does not independently prohibit or restrict the use of hazardous chemicals. Instead, it serves as a basis for regulatory obligations in other specific regulations. This study investigates the regulatory implications of meeting hazard criteria under the CLP across EU regulations and directives listed in EU Chemicals Legislation Finder (EUCLEF). The results show that fulfilling criteria for human health hazard classes trigger regulatory obligations in the highest number of regulations/directives, with carcinogenicity, mutagenicity, and reproductive toxicity (CMR) leading to obligations in 19 of 20 pieces of legislation linked to the CLP. Conversely, physical, environmental, and ozone layer hazards are associated with fewer regulations and directives, and lead to fewer prohibitions. The study underscores the pivotal role of the CLP in EU chemical legislation and the need for coherence and consistency across regulations. While regulatory obligations are primarily aimed at substances meeting hazard criteria, the variability in self-classification notifications and limitations in harmonized classification processes were observed. Moreover, the complexity of the regulatory structure poses challenges for stakeholders and policymakers, including inconsistencies, compliance difficulties, and the need for frequent revisions. Addressing these challenges is critical for enhancing regulatory effectiveness and ensuring a more coherent and harmonized approach to chemical management in the EU. [ABSTRACT FROM AUTHOR]

Introduction Methods Results Conclusions The Medtronic Micra VR and Abbott AVEIR VR are the leadless pacemakers (LPM) currently available in the United States (US). Micra VR employs fixation tines and the AVEIR VR uses an active fixation helix. Micra VR requires fixation before electrical measurements are obtained, while R‐waves may be mapped by AVEIR VR without fixation. Little comparative data is available for these LPMs. Accordingly, we compared the incidences of procedure‐related major adverse clinical events (MACE) and device problems in the US for Micra VR and AVEIR VR during 2022–2024.We searched the FDA's Manufacturer and User Facility Device Experience (MAUDE) database for US reports of MACE and device problems that were filed from April 2022 to December 2023 for AVEIR VR, and from June 2022 to April 2024 for Micra VR. Totals for US‐registered LPM implants were obtained from the manufacturers' product performance reports.During the study period, 5990 AVEIR VR and 10 940 Micra VR implants were registered in the US. We found 305 MAUDE reports for AVEIR VR (5.1%), versus 541 MAUDE reports for Micra VR (4.9%) (p = .702). The incidence of MACE was 0.72% (43/5990) for AVEIR VR versus 0.59% (65/10 940) for Micra VR, (p = .387). The incidences of procedure‐related death, cardiac perforation. cardiac arrest, emergency pericardial drainage or reparative surgery were similar for both LPMs (p > .05). Micra VR had more unacceptable thresholds requiring LPM replacement compared to AVEIR VR (95;0.9% vs. 24;0.4%; p = .001). AVEIR VR had a statistically higher incidence of device dislodgement during (32) and after (21) implant compared to Micra VR (53 (0.9%) vs. 46 (0.4%), p < .001).Micra VR and AVEIR VR have similar procedural safety profiles, including the incidences of death and perforation. However, device problems differed significantly, possibly related to their design differences. Compared to Micra VR, AVEIR VR appears to have an advantageous threshold measurement capability but is more prone to device dislodgement. [ABSTRACT FROM AUTHOR]

The geographical dispersion of collaborative factories can provide cost-saving potential for manufacturers and lead them to easier fit the global markets. On the other hand, in such networks of factories, coordination is especially important for the just-in-time delivery of orders. This study investigates a new configuration of factories in a network of collaborative manufacturing. In the first stage, some independent suppliers produce and deliver the different components of the final products to the assembly factory. Each supplier can produce a particular component of a final product. In the assembly factory, the final products are assembled. The objective is to determine the optimal schedule of the jobs in each factory to minimize the sum of earliness and tardiness. A mixed-integer formulation for this problem is proposed, which can find the optimal solution for the small-size instances. The iterated local search methods are also developed to cope with larger instances. Computational experiments show that the iterated local search methods outperform the well-known iterated greedy method in literature. [ABSTRACT FROM AUTHOR]

This paper proposes development of optimized heterogeneous ensemble models for prediction of responses based on given sets of input parameters for wire electrical discharge machining (WEDM) processes, which have found immense applications in many of the present-day manufacturing industries because of their ability to generate complicated 2D and 3D profiles on hard-to-machine engineering materials. These ensembles are developed combining predictions of the three base models, i.e. random forest, support vector machine and ridge regression. These three base models are first framed utilizing the training datasets, providing predictions for all the responses under consideration. Based on these predictions, two optimization problems are formulated for each of the responses, while minimizing root mean squared error and mean absolute error, for subsequent development of two optimized ensembles whose predictions are the weighted sum of the predictions of the base models. The prediction performance of all the five models is ascertained through nine statistical metrics, after which a cumulative quality loss-based multi-response signal-to-noise (MRSN) ratio for each model is computed, for each of the responses, where a higher MRSN ratio indicates greater accuracy in prediction. This study is conducted using two experimental datasets of WEDM process. Overall, the optimized ensemble models having higher MRSN ratios than the base models are indicated to deliver better prediction accuracy. [ABSTRACT FROM AUTHOR]

Pectin, an acidic polysaccharide, is naturally present primarily in the cell walls and inner layers of higher plants. Pectin is extensively used in food, pharmaceutical, cosmetic, and other industries owing to its exceptional attributes encompassing superior gelation, emulsification, antioxidant activity, stability, biocompatibility, and nontoxicity. Due to the increasing demand for pectin, there is a short supply in the domestic pectin market. Currently, the domestic production of pectin is heavily reliant on imports, thus emphasizing the urgent need to enhance its local manufacturing capabilities. Due to the diverse sources of pectin and variations in extraction and purification methods, its content, physicochemical properties, and biological activity are influenced, consequently impacting the market application of pectin. Therefore, this paper comprehensively reviews the extraction and purification process of pectin, in vivo metabolism, and biological activities (including antitumor, immunomodulatory, anti‐inflammatory, antioxidant, hypoglycemic and hypolipidemic effects, antimicrobial properties, accelerated wound healing potential, promotion of gastrointestinal peristalsis, and alleviation of constipation as well as cholesterol‐lowering effect). Furthermore, it explores the diverse applications of pectin in food science, biomedicine, and other interdisciplinary fields. This review serves as a valuable resource for enhancing the efficiency of pectin content improvement and exploring the potential value and application of pectin in a more scholarly and scientifically rigorous manner. [ABSTRACT FROM AUTHOR]