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Available information for evaluating the possibility of hospitality firm failure in emerging countries is often deficient. Oversampling can compensate for this but can also yield mixed samples, which limit prediction models’ effectiveness. This research aims to provide a feasible approach to handle possible mixed information caused by oversampling.

This paper uses mixed sample modelling (MSM) when evaluating the possibility of firm failure on enlarged hospitality firms. The mixed sample is filtered out with a mixed sample index through control of the noisy parameter and outliner parameter and meta-models are used to build MSM models for hospitality firm failure prediction, with performances compared to traditional models.

The proposed models are helpful in predicting hospitality firm failure in the mixed information situation caused by oversampling, whereas MSM significantly improves the performance of traditional models. Meanwhile, only partial mixed hospitality samples matter in predicting firm failure in both rich- and poor-information situations.

This research is helpful for managers, investors, employees and customers to reduce their hospitality-related risk in the emerging Chinese market. The two-dimensional sample collection strategies, three-step prediction process and five MSM modelling principles are helpful for practice of hospitality firm failure prediction.

This research provides a means of processing mixed hospitality firm samples through the early definition and proposal of MSM, which addresses the ranking information within samples in deficient information environments and improves forecasting accuracy of traditional models. Moreover, it provides empirical evidence for the validation of sample selection and sample pairing strategy in evaluating the possibility of hospitality firm failure.

The purpose of this paper is to provide new insights for managing knowledge reuse in terms of the duality of innovator personality. Continuously developing new products is crucial for firms to maintain and enhance their competitive advantages. However, the limited and highly specialized knowledge can cause innovators of firms to face difficulties in the process of new product development (NPD). In this setting, knowledge reuse becomes a solution that may benefit innovators to overcome the innovation dilemma. Given the fact that innovators with different personality are likely to form incongruent cognitions and affection on knowledge reuse, thus subsequently affecting the performance of NPD, there is an urgent need to investigate the effects of innovator personality in the entire process of knowledge reuse.

This paper exploits five-factor model (FFM) of personality to comprehensively investigate the dual effects of innovator personality in managing knowledge reuse based on the two distinct sets of knowledge reuse initiation and implementation.

By using the data from 981 innovators of knowledge-intensive firms in China, this study finds that the FFM traits of conscientiousness and agreeableness had opposing effects on initiation and implementation of knowledge reuse. While the FFM traits of emotional stability and openness to experience both positively affect the knowledge reuse initiation and implementation. Moreover, the FFM traits of extraversion benefit the shaping of knowledge reuse initiation whereas encumbering the implementation of knowledge reuse.

First, this study reveals the different roles of cognitive and affective traits of personality in shaping knowledge reuse. Second, this study exposes the role of innovator personality in determining the performance effects of knowledge reuse implementation. Third, this study highlights the dual effects of innovator personality in managing knowledge reuse. This study offers evidence for arranging the innovators with appropriate FFM traits in various stages of knowledge reuse.

The purpose of this paper is to develop a multi-agent-based simulation model for the online opinion dissemination during hazardous chemical leakage emergencies into rivers in China, to explore an appropriate crisis information release policy of China’s government for controlling public panic.

In the proposed model, two fundamental attributes of crisis information, i.e., truthfulness (for true or false news) and attitude (for positive, neutral or negative opinion), are considered. Four major agents in the online community system, i.e., citizens, the government, media and opinion leaders, are included. Using four typical accidents of hazardous chemical leakage into rivers in China as case studies, insightful policy implications can be obtained for crisis management and panic control.

The news about the terrible potential damages from such a type of accidents will instantly arise wide-ranging public panic; therefore, the corresponding crisis information release policy should be carefully designed. It is strongly advised against publishing false news to temporarily conceal the accidents, which will seriously hurt the government’s reputation and agitate much larger-scale public panic in terms of degree and duration. To mitigate public panic, the true news especially about treatment measurements should be published immediately. If the government does nothing and releases no crisis information, the public panic will go out of control.

This paper only focuses on the crisis information release policies from the perspectives of the government. Furthermore, this study especially focuses on the cases in China, and extending the proposed model study for general contexts is an important direction to improve this study. Finally, the proposed model should be extended to other types of emergencies to further justify its generalization and universality, especially various natural catastrophes like storms, floods, tsunamis, etc.

This paper develops a multi-agent-based model for online public opinion dissemination in emergency to explore an appropriate crisis information release policy for controlling public panic stemming from hazardous chemicals leakage accidents into rivers. The proposed model makes major contributions to the literature from two perspectives. First, the crisis information about emergency accidents are divided into true and false news based on the truthfulness attribute, and into neutral, positive and negative emotions based on the attitude attribute. Second, the proposed model covers the main agents in the online virtual community.

This study aims to investigate whether Industry 4.0 digital technologies can enhance the effects of lean production on social performance.

Survey data collected from China’s manufacturing industry are used to test research hypotheses.

The results reveal that the three dimensions of lean production (internal, customer and supplier) have a significant positive effect on social performance and that digital technology advancement (DTA) positively moderates these relationships. DTA adds only a marginal contribution to social performance.

This study addresses a new challenging question from manufacturing firms: how to integrate lean, technology and people? The empirical findings provide timely and insightful practical guidance for managers to better understand the role of digital transformation in the traditional lean context.

While digitalization is known to complement lean production, this study shows digitalization also complements the effects of lean production on social performance.

To address the critical sustainability challenges currently faced by China, manufacturers in this country have committed to improve their environmental performance. To support this commitment, evidence suggests that Chinese manufacturers have mainly turned to the implementation of environmental management approaches such as ISO 14001, cleaner production, green supply chain management, circular economy and green lean. However, the adoption of other approaches such as total quality environmental management (TQEM) by Chinese manufacturers is less clear. The purpose of this paper is to fill this gap by providing light into fundamental issues regarding the implementation of TQEM in the manufacturing sector of China.

A survey-based exploratory study was conducted based on 119 Chinese manufacturing companies, and the data obtained were analysed using a combination of descriptive and inferential statistics.

The results revealed that in general, there is less awareness of TQEM in the Chinese manufacturing sector than other environmental and quality/operations improvement approaches such as green supply chain management, reverse logistics, ISO 9000, Six Sigma and lean Six Sigma. Thus, its degree of implementation is also lower than these approaches as well as ISO 14001. The results also indicate that although a company’s size is not associated with the implementation of TQEM, it is mainly large organisations and those that have adopted TQM those which will be mainly aware and have implemented TQEM. The study also reveals the drivers, results and challenges of TQEM implementation.

The paper extends the currently limited knowledge on TQEM, and its results are beneficial for managers who aim at effectively adopting TQEM to simultaneously improve the environmental, operational and financial performance of their organisations. The paper can also motivate organisations not currently embarked on the “green wagon” to contemplate the benefits that implementing TQEM, or any other environmental management approach, may bring to their operations and business.

For prefabricated building construction, improper handling of the production scheduling for prefabricated components is one of the main reasons that affect project performance, which causes overspending, schedule overdue and quality issues. Prior research on prefabricated components production schedule has shown that optimizing the flow shop scheduling problem (FSSP) is the basis for solving this issue. However, some key resources and the behavior of the participants in the context of actual prefabricated components production are not considered comprehensively.

This paper characterizes the production scheduling of the prefabricated components problem into a permutation flow shop scheduling problem (PFSSP) with multi-optimization objectives, and limitation on mold and buffers size. The lean construction principles of value-based management (VBM) and just-in-time (JIT) are incorporated into the production process of precast components. Furthermore, this paper applies biogeography-based optimization (BBO) to the production scheduling problem of prefabricated components combined with some improvement measures.

This paper focuses on two specific scenarios: production planning and production rescheduling. In the production planning stage, based on the production factor, this study establishes a multi-constrained and multi-objective prefabricated component production scheduling mathematical model and uses the improved BBO for prefabricated component production scheduling. In the production rescheduling stage, the proposed model allows real-time production plan adjustments based on uncertain events. An actual case has been used to verify the effectiveness of the proposed model and the improved BBO.

With respect to limitations, only linear weighted transformations are used for objective optimization. In regards to research implications, this paper considers the production of prefabricated components in an environment where all parties in the supply chain of prefabricated components participate to solve the production scheduling problem. In addition, this paper creatively applies the improved BBO to the production scheduling problem of prefabricated components. Compared to other algorithms, the results show that the improved BBO show optimized result.

The proposed approach helps prefabricated component manufacturers consider complex requirements which could be used to formulate a more scientific and reasonable production plan. The proposed plan could ensure the construction project schedule and balance the reasonable requirements of all parties. In addition, improving the ability of prefabricated component production enterprises to deal with uncertain events. According to actual production conditions (such as the occupation of mold resources and storage resources of completed components), prefabricated component manufacturers could adjust production plans to reduce the cost and improve the efficiency of the whole prefabricated construction project.

The value of this article is to provide details of the procedures and resource constraints from the perspective of the precast components supply chain, which is closer to the actual production process of prefabricated components. In addition, developing the production scheduling for lean production will be in line with the concept of sustainable development. The proposed lean production scheduling could establish relationships between prefabricated component factory manufacturers, transportation companies, on-site contractors and production workers to reduce the adverse effects of emergencies on the prefabricated component production process, and promote the smooth and efficient operation of construction projects.

The purpose of this paper is to present an analysis of research on lean focusing on barriers in its implementation through a systematic literature survey.

A literature survey of peer-reviewed journal articles, survey reports, master theses, doctoral theses and paradigmatic books with managerial impact is used as the research methodology.

The findings derived from the evaluation of the publications analyzed have led to the identification of 24 lean barriers. The success of lean implementation will not be entirely based on application of appropriate tools and techniques alone but also on the top managements' involvement and leadership, workers' attitude, resources and the organizational culture.

This literature survey is primarily focused on lean implementation in the manufacturing sector.

This paper explores barriers for successful lean implementation and provides a concise description of the barriers that will be helpful for further studies in the domain of lean manufacturing.

Government of many countries around the world is encouraging and helping small- and medium-scale industries to understand and implement lean systems by preparing accessible database of lean consultants, providing financial assistance for training by professionals and establishing professional associations. However, many industries experienced failure in lean implementation. This research work provides a launching pad to develop a strategy to tackle barriers for successful lean implementation.

This paper puts forward the key barriers that should be tackled for successful lean implementation. It might represent new opportunities for rigorous and relevant research that would contribute to more translucent knowledge of lean being gained.

In software development (SD), practitioners have realized the importance of lean thinking. A new term “Leagile” is coined, which is an integrated approach of traditional lean and agile thinking to managing the operations. The study aims to investigate the application of the Leagile principles in a new sector and establish a relationship between the adoption of Leagile approach and operational performance (OP) in SD organizations.

Empirical research is conducted to investigate the linkage between the Leagile principles and operational measures. Data is collected through surveys from 256 SD industries located in 11 states of India and analysed using the structural equation modelling approach.

The practitioners envisage a positive impact of adoption of Leagile principles on OP of SD organizations, but one of the principles, i.e. perfection, is unable to influence the performance.

The study contributes by authorizing the contribution of Leagile principles towards OP of SD organizations. The outcomes will motivate the practitioners to enhance the adoption of Leagile principles in SD organizations.

Spark ignition (SI) engines are used in a wide area in the transportation industry, from road vehicles to piston-prop aircraft. On the other hand, the decrease in reserves of fossil fuels used in SI engines and the increase in greenhouse gas emissions makes the use of alternative fuels inevitable. In this paper, optimization of in-cylinder combustion and engine performance parameters by intake-charge conditions [i.e. intake-air temperature, injection timing and exhaust gas recirculation (EGR)] in a hydrogen (H₂)-fueled small SI engine is performed.

Experimental studies were performed at a 1,600 rpm engine speed of a single-cylinder, air-cooled engine having a stroke volume of 476.5 cm³, maximum output power of 13 HP and torque of 25 Nm. The hydrogen-fueled SI engine was operated by a lean air-fuel mixture (ϕ = 0.6) under wide-open throttle (WOT) conditions.

The findings of the paper show that improvements can be achieved in in-cylinder combustion, indicated engine performance, exhaust NO_x emissions with optimum intake-air temperature, the start of H₂ injection and the ERG rate.

It has been determined that a 32°C intake-air temperature, 395°C (bTDC) start of H₂ injection, and 5%–10% EGR rates are the most suitable values for the examined hydrogen fueled SI engine.

Hydrogen is a usable alternative fuel for SI engines used in a wide area from road vehicles to piston-prop aircraft engines. However, a number of problems remain that limit hydrogen fueled SI engines to some extent, such as backfire, a decrease of engine power, and high NO_x emissions. Therefore, it is appropriate to examine the effects of intake-charge conditions on in-cylinder combustion, engine performance, and NO_x emissions parameters in a hydrogen fuelled SI engine.