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The purpose of this paper is to propose that the effectiveness of organizational design-manufacturing integration (ODMI) practices is contingent upon the degree of complexity of the manufacturing environment. The paper submits that the level of use of ODMI ought to match the level of complexity of the manufacturing environment. The paper puts forward the hypothesis that when a misfit occurs between ODMI and complexity (high use of ODMI practices in low complexity environments or low use of ODMI practices in high complexity environments) manufacturing operational performance declines.

The paper tests the hypothesis based on a survey database of 725 manufacturers from 21 countries. The measurement model was assessed with confirmatory factor analysis and the hypothesis was tested with linear regression.

A misfit between the level of ODMI use (job rotation and co-location) and manufacturing complexity (product and process complexity) has a negative effect on manufacturing operational performance dimensions of quality, delivery and flexibility. Post hoc analyses also suggest that firms that operate in different environments in what concerns the rate of change in process technologies suffer differentiated negative impacts of ODMI-complexity misfit.

Future studies could extend this research to other dimensions of design-manufacturing integration, such as technological practices.

Manufacturers with high levels of complexity should invest strongly in ODMI practices. However, manufacturers with low levels of complexity should invest in these practices with caution since the expected payoffs may not outweigh the effort.

The study assesses fit as a simultaneous set of contingency factors, applying profile-deviation analysis to ODMI and operational performance relationships. By focusing on plant-level manufacturing complexity, this study complements existing studies of product development complexity which tend to focus on project-level complexity.

The purpose of this paper is to test whether complexity interacts with Sales and Operations Planning (S&OP) practices by positively moderating the impact of S&OP practices on manufacturing operational performance dimensions of quality, flexibility and delivery.

Three hypotheses are developed on the relationships between S&OP practices, task complexity and process complexity and manufacturing operational performance. Scales are validated with structural equation modelling. The hypotheses are tested through a hierarchical regression analysis using data from a sample of 725 manufacturing plants from 21 countries.

S&OP practices of organizational management, technological integration, measurement systems and integration of plans impact positively on manufacturing operational dimensions of quality, delivery and flexibility. Process complexity moderates the effect of S&OP practices, amplifying its impact upon all three performance dimensions. Product complexity moderates the effect on quality, but not on delivery and flexibility.

S&OP practices of organizational and technological coordination of manufacturing and new product design; information technology to measure information sharing and planning; dedicated information systems do impact upon manufacturing operational performance. Results are amplified by process complexity. The more complex are the manufacturing processes the larger the gains of S&OP.

This research applies contingency theory to S&OP and empirically demonstrates its impact on manufacturing operational performance and the moderator role of complexity.

As the increase in manufacturing competitiveness forces organizations to use more sophisticated and complex software, system performance depends on clever systems design, efficient planning and scheduling of the related processes. For these advanced manufacturing systems the dependence on human competence is greater. However, previous studies indicate that the human aspects for successfully implementing such systems have been neglected. The objective here is to test the hypotheses that system complexity is inversely related to performance, and that training of system operators, and the quality of the man/machine interface reduces the negative impact of system complexity. A sample of discreet manufacturing systems from 128 organizations was used to test these hypotheses empirically. Moderated multivariate regression indicates that man/machine interfaces are significant contributors to reducing the negative effect of systems complexity. With a lower level of significance, operator training has a similar impact. For complex manufacturing systems software, it behoves managers to insure that the man/machine interface provides the desirable features outlined in this study.

The purpose of this paper is to examine the nuanced effects of downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. Intelligent manufacturing is considered to clarify their boundary conditions.

The ordinary least squares regression was conducted, based on the data collected from 136 high-tech firms in China.

Horizontal downstream complexity has a positive effect on supply chain resilience significantly, while the negative impact of vertical downstream complexity on supply chain resilience is not significant. Contingently, intelligent manufacturing plays a negative moderating role in the relationship between horizontal downstream complexity and supply chain resilience, while it positively moderates the relationship between vertical downstream complexity and supply chain resilience.

This study disentangles the nuanced effects of both horizontal and vertical downstream complexity on supply chain resilience, based on portfolio theory and normal accident theory. It also clarifies their boundary conditions by considering the focal firm's intelligent manufacturing level as the contingent factor.

This paper aims to propose a multi-dimensional model on the basis of the key factors of the flexibility and the complexity through structural equation modeling (SEM). Dimensions of the flexibilities and complexity, including 16 main factors and 34 sub-factors, are investigated. The sampling of the research is accomplished using both academic and industrial experts.

A huge electronic questionnaire analysis, including 1,250 samples from which 1,036 were returned, was accomplished in various universities and manufacturing companies throughout the USA, Europe and Asia. Partial least square-SEM (PLS-SEM) is used to test the hypotheses through confirmatory factor analysis.

The results reveal insightful information about the impacts of different dimensions of flexibility on each other and also the effect of the flexibility on the complexity. Finally, system of linear mathematical equations for flexibility-complexity trade-off is proposed. This can be applied to realize the trade-off among dimensions of flexibility and complexity.

Flexible manufacturing systems are formed to meet the needs of the customers. Such systems try to produce products in appropriate quality at the right time and at the specified quantity. These, in turn, require flexibility and will cause complexity. Although flexibility and complexity are both important, there is no comprehensive framework in which the multi-dimensional relationships of the manufacturing flexibility and complexity, as well as their dimensions, are demonstrated.

Increasingly, dynamic market environments lead to growing complexity in manufacturing and pose a severe threat for the competitiveness of manufacturing companies. Systematic guidance to manage this complexity, especially in the context of Industry 4.0 and the therewith rising trends such as digitalization and data-driven production optimization, is lacking. To address this deficit a case-based reasoning (CBR) system for providing knowledge about managing complexity in Industry 4.0 is presented.

First, the explicit knowledge representation for managing complexity in IT-based manufacturing is introduced. Second, the CBR process step to retrieve knowledge from an artificially composed case base with in total 70 cases of data-based complexity management in the context of Industry 4.0 is set out. Third, knowledge transfer alongside several maturity levels of information technology capabilities of manufacturing systems for reuse in new problem scenarios is introduced.

The paper comprises the conceptual approach for designing a CBR system to support data-based complexity management in manufacturing systems. Furthermore, the appropriateness of the CBR system to provide applicable knowledge for reducing and managing complexity in corporate practice is shown.

The presented research results are evaluated in the course of an embedded single case study and may therefore lack generalizability. Future research to test and enhance the appropriateness of the developed CBR system will strengthen the research contribution.

The paper provides a novel approach to systematically support knowledge transfer for data-based complexity management by transferring the well-known and established methodology of CBR to the rising application domain of manufacturing systems in the context of Industry 4.0.

Based on a conceptual framework of the linkages between strategic manufacturing goals and complexity, the purpose of this paper is to investigate adaptation processes in manufacturing firms to increasing external complexity.

Hypotheses are tested with statistical analyses (group comparisons and structural equation models) that are conducted with data from the third round of the International Manufacturing Strategy Survey.

The study shows that manufacturing firms face different degrees of complexity. Firms in a more complex environment tend to possess a more complex internal structure, as indicated by process configuration, than firms in a less complex environment. Also depending on the degree of complexity, different processes of adaptation to increases in external complexity are initiated by organisations.

Research studies taking into account the dynamics of adaptation processes would be helpful in order to draw further conclusions, for instance, based on longitudinal analyses or simulation studies.

Depending on the level of complexity a firm has been confronted with in the past, different adaptation processes to further growing complexity can be initiated. Firms in high complexity environments have to re‐configure their strategic goals; firms in low complexity environments have to build‐up internal complexity to cope with demands from the outside.

The paper distinguishes between adaptation processes in low and high complexity environments and provides explanations for the differences.

Presents a model that hypothesizes relationships between logistical complexity and both the importance of JIT manufacturing and the most appropriate organization structure for implementing JIT manufacturing. Logistical complexity can be defined in terms of the number of manufacturing steps or the number of different part numbers handled in a factory. Hypothesizes that the greater a factory′s logistical complexity, the greater the importance of JIT manufacturing and the greater the interdependences between different manufacturing steps and people and thus the greater the need for co‐ordinating mechanisms.

This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

The recent shift towards accommodating flexibility in manufacturing companies and the complexity resulting from product variety highlight the significance of flexible assembly systems and designing products for them. The purpose of this paper is to provide insight into the requirements of a flexible assembly system for product design from the assembly system’s standpoint.

To fulfil the purpose of the paper, a literature review and a case study were performed. The case study was conducted with an interactive research approach in a global market leader company within the heavy vehicle manufacturing industry.

The findings indicate that common assembly sequence, similar assembly interfaces, and common parts are the main requirements of a flexible assembly system for product design which reduce complexity and facilitate various flexibility dimensions. Accordingly, a model is proposed to broaden the understanding of these requirements from the assembly system’s standpoint.

This study contributes to the overlapping research area of flexible assembly systems and product design.

The proposed model is largely based on practical data and clarifies the role of product design in facilitating flexibility in an assembly system. It can be used by assembly managers, assembly engineers, and product designers.

The key originality of this paper compared to the previous studies lies in presenting a novel assembly-oriented design model. The model enhances understanding of a flexible assembly system’s requirements for product design with regard to reducing complexity and managing variation in a flexible assembly system. These requirements can be applied to product design across various product families within a company’s product portfolio.