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The purpose of this paper is to investigate a novel generalised grey target decision method (GGTDM) with index and weight involving mixed attribute values.

The mixed attribute values are transformed into binary connection numbers and also comprised of two-tuple (determinacy, uncertainty) numbers to fulfil the decision-making task. The proposed method constructs the weight function to convert the mixed attribute-based weights into the certain number-based weights and determines the alternatives ranking by the comprehensive weighted Gini–Simpson indices (CWGSIs).

The result of decision making regarding the numerical example by the proposed approach is somewhat different from that obtained by the reported vector-based method. The reasons for this are threefold: the decision-making bases are different, the target centre indices are determined by different mechanisms and certain number-based weights are calculated in different ways.

The proposed method ranks an alternative based on the Gini–Simpson index, as derived from the viewpoint of measuring the uncertainty (heterogeneity): however, the vector-based GGTDM makes a decision based on proximity, as is the case when measuring the similarities between index vectors.

The proposed approach is admissible to solving mixed attribute-based decision making especially for alternative indices and attribute weights containing both uncertain numbers.

The proposed method provides a new perspective on measuring the difference of alternatives to the target centre via the CWGSI: the CWGSI is obtained by relying on the pseudo-probabilities achieved by the ratios of the alternative indices to the target centre indices. It also builds a weight function converting the mixed attribute-based weights into certain number-based weights. This method provides a framework that should be tested in terms of its effective decision making using real data and an actual problem.

This paper is to propose a novel generalized grey target decision method (GGTDM) with index and weight both containing mixed types of data.

The decision-making steps of the proposed approach are as follows. First, all mixed attribute values of alternatives and weights are transformed into binary connection numbers and also comprised two-tuple (determinacy, uncertainty) numbers. Then, the two-tuple (determinacy, uncertainty) numbers of target center indices are calculated. Next, the certain weights are determined by the Gini–Simpson (G–S) index-based method. Following this, the comprehensive-weighted Kullback–Leibler distances (CWKLDs) of all alternatives and the target center are obtained. Finally, the alternative ranking relies on the CWKLD considering the smaller value as the better option.

The certain weights determined by the improved Gini–Simpson index (IGSI) based method are more accurate in compared with that by the proximity-based method and the weight function method. The discrimination ability of alternatives ranking of the proposed approach is stronger than that of the compared comprehensive-weighted proximity (CWP) based method and comprehensive-weighted Gini–Simpson index (CWGSI) based method.

The proposed method fulfills the decision-making task relying on CWKLD, which solves the uncertain measurement from the viewpoint of entropy.

The proposed approach adopts the IGSI to transform uncertain weights into certain ones and takes the CWKLD as the basis for the decision-making.

The purpose of this paper is to develop the method of generating assembly sequences, which can be used in the shipbuilding industry. The method must take into account the assumptions specific for assembly processes of large-size steel ship hulls, among others, a large number of connections, multi-stage and parallel assembly, set priority relations between connections.

The assembly sequence is presented as a directed acyclic graph, whose vertices are mutually uniquely assigned to connections on a hull structure. The minimization of the number of unmet priority precedence of performing connections has been proposed as a criterion of optimization. The genetic algorithm has been proposed as a method to solve problems.

The proposed method allows to model the acyclic assembly process of welded structures and find solutions minimizing the objective function even for very complex problems. Because of this, the method has a chance to be used in shipbuilding.

Mathematical formulation of priority assumptions is quite laborious. The possibility of partial automation of this process should be considered. Due to the complexity of the problem, a relatively simplified objective function has been proposed. In assembling a hull, additional criteria should be taken into account. It is the direction of further research.

The method can be successfully used in shipbuilding and in planning the production of other steel welded structures, among others, tanks, components of bridges, offshore structures. Examples of calculations were performed on an actual structure of a hull fragment.

A new way of coding the acyclic serial-parallel sequence was designed. The proposed method allows to analyse the sequence using the graph theory. Original, two-part crossover and mutation operators for assembling sequence were proposed.

In this paper, an assembly sequence planning system, based on binary vector representations, is developed. The neural network approach has been employed for analyzing optimum assembly sequence for assembly systems.

The input to the assembly system is the assembly's connection graph that represents parts and relations between these parts. The output to the system is the optimum assembly sequence. In the constitution of assembly's connection graph, a different approach employing contact matrices and Boolean operators has been used. Moreover, the neural network approach is used in the determination of optimum assembly sequence. The inputs to the networks are the collection of assembly sequence data. This data is used to train the network using the back propagation (BP) algorithm.

The proposed neural network model outperforms the available assembly sequence‐planning model in predicting the optimum assembly sequence for mechanical parts. Due to the parallel structure and fast learning of neural network, this kind of algorithm will be utilized to model another types of assembly systems.

In the proposed neural approach, the back propagation algorithm is used. Various training algorithms can be employed.

The simulation results suggest that the neural predictor would be used as a predictor for possible practical applications on modeling assembly sequence planning system.

This paper discusses a new modelling scheme known as artificial neural networks. The neural network approach has been employed for analyzing feasible assembly sequences and optimum assembly sequence for assembly systems.

The purpose of the paper is to develop a method of automatic classification of the components of the assembly units. The method is crucial for developing an automatic ship assembly planning tools. The proposed method takes into account the assumptions specific for shipbuilding technology processes: high complexity of structures, difficult expert-based classification of components, fixed priority relations between connections resulting from geometrical constraints and demands of welding processes.

The set of ex post determined liaisons and assembly sequences constitutes the database of structures which have been made-up earlier. The components classification problem is solved using matrix coding of graphs. Information in such form is stored in the database. The minimization of number of cycles in the graph of classes sequence and minimization of diversity of classes within all constructions has been proposed as criteria of optimization. The genetic algorithm has been proposed as a solution method.

The proposed method solves the problem of components’ classifications. It allows setting the pattern of priorities between classes of various connections. This gives a chance to determine the relationship constraints between the connections of new structures for which assembly sequences are not established.

Mathematical formulation of the database is quite laborious. The possibility of partial automation of this process should be considered. Owing to the complexity of the problem, a relatively simple objective function has been proposed. During a ship hull assembly, additional criteria should be taken into account, what will be the direction of further research.

Automatic classification of components is dedicated for implementation in shipyards and similar assembly systems. Tests performed by the authors confirm efficiency of presented method in supporting management of the database and assembly of new structures planning. Suggested activity-oriented approach allows for easy conversion of any assembly unit structure to the form of a matrix.

The new approach for components classification according to its assembly features distinguishes the proposed method from others. The use of nilpotent matrix theory in an acyclicity of graphs analysis is also a unique achievement. Original crossover and mutation operators for assembly sequence were proposed in the article.

The purpose of this paper is to enhance the method developed by previous researchers. In addition to using the combined interference matrix, the combined connection matrix and the combined contact matrix of product components, the disassembly sequence matrix and the combined instability matrix with platform to evaluate instability of sub‐assemblies are built, and effects of changes of sub‐assembly disassembly directions or tools and the effect of gravity are considered to obtain the best disassembly sequence for a product with many components. A computer program is generated and results of two cases are compared with those of the available studies.

The methodology includes the combined interference matrix, the combined contact matrix and the combined connection matrix of components for a product. The combined instability matrix of sub‐assemblies, changes of sub‐assembly disassembly direction or tools, and the effect of gravity during operation are considered. The binary number system is used to simplify relations among components of a product.

This methodology enhances the existing method and software is generated. Results of two cases are compared and show the same optimum disassembly processes as those obtained from other researchers.

All matrices are defined by the directions of x, y and z with three axes perpendicular to each other. The computer program generated cannot be used for a product with components that must be disassembled in the directions different from the axes.

Two cases are used to investigate feasibility of the proposed methodology with the computer program generated. The first one is an electric drill, and the second one is a flash lighter.

The methodology described in this paper is feasible for study of disassembly processes of products. The software generated can be used to obtain the optimum disassembly process of products.

Purpose: Previous research identified a measurement gap in the individual assessment of social misconduct in the workplace related to gender. This gap implies that women respond to comparable self-reported acts of bullying or sexual discrimination slightly more often than men with the self-labeling as “bullied” or “sexually discriminated and/or harassed.” This study tests this hypothesis for women and men in the scientific workplace and explores patterns of gender-related differences in self-reporting behavior.

Basic design: The hypotheses on the connection between gender and the threshold for self-labeling as having been bullied or sexually discriminated against were tested based on a sample from a large German research organization. The sample includes 5,831 responses on bullying and 6,987 on sexual discrimination (coverage of 24.5 resp. 29.4 percentage of all employees). Due to a large number of cases and the associated high statistical power, this sample for the first time allows a detailed analysis of the “gender-related measurement gap.” The research questions formulated in this study were addressed using two hierarchical regression models to predict the mean values of persons who self-labeled as having been bullied or sexually discriminated against. The status of the respondents as scientific or non-scientific employees was included as a control variable.

Results: According to a self-labeling approach, women reported both bullying and sexual discrimination more frequently. This difference between women and men disappeared for sexual discrimination when, in addition to the gender of a person, self-reported behavioral items were considered in the prediction of self-labeling. For bullying, the difference between the two genders remained even in this extended prediction. No statistically significant relationship was found between the frequency of self-reported items and the effect size of their interaction with gender for either bullying or sexual discrimination. When comparing bullying and sexual discrimination, it should be emphasized that, on average, women report experiencing a larger number of different behavioral items than men.

Interpretation and relevance: The results of the study support the current state of research. However, they also show how volatile the measurement instruments for bullying and sexual discrimination are. For example, the gender-related measurement gap is considerably influenced by single items in the Negative Acts Questionnaire and Sexual Experience Questionnaire. The results suggest that women are generally more likely than men to report having experienced bullying and sexual discrimination. While an unexplained “gender gap” in the understanding of bullying was found for bullying, this was not the case for sexual discrimination.

This paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.

The authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.

The authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).

This paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

In this study, we examine the relationship between political connections of private firms and the initial public offering process. Using registration statement information, we create a unique database of politically connected IPO firms. We find that political connections are substitutes to high-quality underwriters and big four auditors. Politically connected firms manage earnings more highly upward than non-connected firms prior to the public offering. Politically connected firms also exhibit less underpricing than non-connected firms. Finally, politically connected IPO firms have superior post-IPO returns relative to non-connected IPO firms.