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This chapter aims to investigate the relationship between levels of subsidiary autonomy and the performance of a subsidiary’s subunit (factory) in Japanese manufacturing subsidiaries in Thailand. We conducted ordinary least squares regression analysis based on a questionnaire survey of 50 Japanese manufacturing subsidiaries in Thailand and multiple case studies to investigate the causal relationship between subsidiary autonomy and factory performance. We have three main findings. First, the autonomy level of Japanese manufacturing subsidiaries is linked to the subsidiaries’ factories’ performance compared to factories in Japan, but not in other foreign countries. Second, high levels of subsidiary autonomy are negatively associated with factory performance. Third, there are two causal relationships: high factory performance leading to low subsidiary autonomy and high/low subsidiary autonomy leading to low/high factory performance. From this, we discussed whether the degree of resource centralization in the home country influences the relationship between the level of subsidiary autonomy and a subunit’s performance in the foreign subsidiary. Moreover, we discussed the possibility that the causal relationships between them are not necessarily direct causal relationships. We identified a new factor determining subsidiary autonomy and investigated the relationship between the subsidiary autonomy and performance of a subunit in the foreign subsidiary compared to the home country. Because this has not been discussed in previous studies, this chapter contributes to the study of headquarters–subsidiary relationships and gives guidelines to practitioners on managing subsidiary autonomy.

Companies are concerned about the well-being of workers in their supply chains, but conventional audits fail to uncover critical problems. Yet, if the happy worker – productive worker thesis is correct, it would benefit factories in fast-developing countries, particularly China which is key to many global supply chains, to ensure the well-being of their workers. The authors set out to better understand the relationship between well-being and performance in four Chinese factories.

Over 12-months the authors collected digital diaries from 466 workers in four factories, and monthly data about the performance of their factories. The authors used this data to gain insights into the well-being of workers in these factories; to design experimental interventions to improve this; and to consider any effects these had on factory performance.

The experiments showed that training interventions to improve workers' well-being through their work relationships and individual skills improved not just a factory's general worker well-being, but also some aspects of its performance and worker retention. Thus, it brought benefits not only for the workers but also for the factory owners and their client companies.

While there is a significant body of research investigating the happy worker – productive worker thesis, this was not conducted in Chinese factories. The authors’ work demonstrates that in this and similar environments, workers' eudaimonic well-being is more important than might be assumed, and that in this context there is a relationship between well-being and performance which can be practically addressed.

This paper demonstrates a multi-criteria analytic hierarchy process (AHP) framework for evaluating and benchmarking maintenance performance in the select agro-based industry.

Initially, 20 maintenance practices (criteria) have been identified after a detailed literature review and discussion with the agro-based industry (sugar, textile and dairy industry) executives. These are then grouped into six maintenance management areas referred to as group criteria. The multi-criteria methodology consists of three steps: criteria identification, hierarchical modeling and data collection and maintenance performance evaluation, and benchmarking. The multi-criteria methodology proposed in this work facilitates two ways of carrying out benchmarking: (1) within the agro-based industry and (2) between the agro-based industry. The methodology has been explained by taking a case example of 45 agro-based industries (18 dairy, 13 sugar and 14 textile) from the western region of India. The sensitivity analysis of the model has been performed to ascertain the robustness of the results.

There is a difference in the maintenance performance across the agro-based industries due to different maintenance practices perceived differently.

The outcome of the model is mainly given by the judgments of the agro-based industry executives. It is also sensitive to any change in the relative importance to the evaluation criteria or the perception about the maintenance performance.

The study contributes in identifying the weakness, if any, by comparing the agro-based industry under investigation with the benchmark factory at three levels, namely, overall performance (factory level), group criteria (maintenance management area level) and criteria (maintenance practice level) allowing further improvement.

The methodology assists in better decision-making and in improving maintenance performance.

Reports recent findings of a two‐phase study investigating new dimensions of manufacturing competitiveness, factory‐based services. Examines relationships between broadly defined service role performance and manufacturing performance. Data were provided by 64 manufacturing firms from the USA, Canada and the UK. Also addresses under what conditions a vital element of such service‐information would be of greatest benefit to the factory’s key internal customer ‐ marketing. A survey of manufacturing and marketing respondents within 32 organizations provides empirical evidence of the positive relationship between factory information measured as a service construct and delivery performance. Anecdotal evidence from interviews provides additional insight into the roles of organizational structure and information technology with respect to the information component of factory‐based service.

Multinational companies have manufacturing operations in various countries; however, there is scarce evidence on how they assess performance of the network-based operations of their factories, called international manufacturing networks (IMN). The purpose of this paper is to propose a process model for the performance assessment of IMNs.

The IMN performance assessment process model was developed from the extant literature and was empirically verified in its congruency and usefulness via a multiple case research. For that, in each case the general process model was derived into a specific application that fit the type of IMN on focus. Qualitative and quantitative data were collected from the case companies’ reports, profiling forms and interviews, followed by within-case and cross-case analyses.

Evidence suggest that the process model, along with its derivations, is a valuable tool to describe and explain how IMN performance assessment unfolds in real organizational environments. Additionally, three propositions emerged: IMN performance assessment has distinct characteristics depending on the type of IMN adopted, which in turn depends on the company’s internationalization strategy; IMN performance assessment has more strategic value and importance for companies that are globally coordinated and adopt “rooted” manufacturing strategies; and companies design their IMN performance assessment on a trial-and-error basis.

As all case-based research, this paper has generalizability limitations. Thus, next steps may include a large-scale survey and an action research that will develop and implement a full-fledged IMN performance assessment.

The process model and descriptive insights provide a diagnostic tool and subsidies that may encourage managers to review and improve their current IMN performance assessment.

The process model contributes to addressing a 20-year gap concerning how to approach IMN performance assessment in a holistic and systematic manner.

Examines the role and influence of management systems, practices and behaviour in successful manufacturing strategy, based on the development of manufacturing strategy into a comprehensive concept which contains three paradigms: manufacturing as a source of competitive advantage, that the choices of manufacturing processes and other related characteristics are contingent on one another, and there is a relationship between best practice and performance. The study employed a survey of 46 Japanese factories in the machinery, electronics and automotive industries, with 26 people in each factory. The factories were examined on how closely they used “best practices” management. In addition, factor analysis, cluster analysis, t‐tests on differences between the groups and correlations among clusters, practices and performance were conducted. The results supported the study’s three hypotheses: factories report different levels of use of the best practices; best practices are linked into certain sets of practices; and the use of best practices is related to performance. The discussion and conclusions address these findings and are used to offer support for Voss’s recent claim that manufacturing strategy should be considered “a continuous loop” among the three paradigms of manufacturing strategy.

This study aims to explore how management accounting practices act as drivers of organizational change in situations of institutional complexity.

A case study was carried out in a small company with a strongly rooted social culture, which was acquired by a large conglomerate and underwent a process of strategic change as part of a new control logic. Based on this, the study analyzes the evolution of this change, with a particular focus on the efforts to construct the meaning of the performance through the inscription of objects from the cultural system to which it is attached and the “situated rationality” of the managers who are involved in its production.

The authors show how managers link their own concepts of performance to accounting practices. At the same time, the authors show how accounting practices unfold through representational gaps that their production generates.

This study acknowledges that bias may arise from reliance on retrospective views of past processes and events, gathered primarily through interviews, documentation and observations.

This study highlights that the way in which the performance concept is presented by accounting practices can have a constructive effect on the organization through the aspirations that its representations entail, thus having the potential to stimulate change in organizations.

This study contributes to the organizational literature by clarifying that accounting practices drive change by providing spaces for debates and questions that affect the way organizations understand and report their performance.

This paper aims to address a distributed assembly permutation flow-shop scheduling problem (DAPFSP) considering budget constraints and factory eligibility. The first stage of the considered production system is composed of several non-identical factories with different technology levels and so the factories' performance is different in terms of processing time and cost. The second stage is an assembly stage wherein there are some parallel work stations to assemble the ready parts into the products. The objective function is to minimize the maximum completion time of products (makespan).

First, the problem is formulated as mixed-integer linear programing (MIP) model. In view of the nondeterministic polynomial (NP)-hard nature, three approximate algorithms are adopted based on variable neighborhood search (VNS) and the Johnsons' rule to solve the problem on the practical scales. The proposed algorithms are applied to solve some test instances in different sizes.

Comparison result to mathematical model validates the performance accuracy and efficiency of three proposed methods. In addition, the result demonstrated that the proposed two-level self-adaptive variable neighborhood search (TLSAVNS) algorithm outperforms the other two proposed methods. Moreover, the proposed model highlighted the effects of budget constraints and factory eligibility on the makespan. Supplementary analysis was presented by adjusting different amounts of the budget for controlling the makespan and total expected costs. The proposed solution approach can provide proper alternatives for managers to make a trade-off in different various situations.

The problem of distributed assembly permutation flow-shop scheduling is traditionally studied considering identical factories. However, processing factories as an important element in the supply chain use different technology levels in the real world. The current paper is the first study that investigates that problem under non-identical factories condition. In addition, the impact of different technology levels is investigated in terms of operational costs, quality levels and processing times.

Rapid product/process realization and enterprise integration have been identified among the major imperatives for enabling the next generation manufacturing paradigm. This paper proposes a virtual factory modeling approach to support these imperatives. A virtual factory is defined as an integrated simulation model of major subsystems in a factory that considers the factory as a whole and provides an advanced decision support capability. It seeks to go beyond the typical modeling of one sub‐system at a time, such as the manufacturing model, the business process model and/or the communication network model developed individually and in isolation. A basic virtual factory model of a semi‐conductor backend factory has been developed for concept demonstration. Application examples are used to demonstrate the integration between business processes and manufacturing system performance. Future work will move further towards the development of the complete virtual factory and its industry applications.

The purpose of this study is to investigate the relationship between investments in quality and lean practices, and their impact on factory fitness. Using concepts originating in the theory of swift even flow, this study asserts that manufacturers, in order to improve their production swiftness and evenness, must leverage the potential synergetic effects between quality and lean practices.

This research uses data from the Global Manufacturing Research Group (GMRG) survey project (with data collected from 922 manufacturing plants, across 18 countries). The constructs and measurement model were assessed using confirmatory factor analysis (CFA) and the hypotheses were tested using ordinary least square (OLS) models.

This study highlights that both investments in quality and lean practices have direct impact factory fitness. The results provide insights into the efficacy of the investments in manufacturing practices and their role in augmenting the operational performance. The investments in quality practices were found to enhance the efficacy of investments in lean practices, which in turn impact the factory fitness.

From a practical perspective, the study informs managers on how to leverage investment in quality practices to enhance the impact of lean practice on performance. The results provide empirical evidence to support management decision-making concerning the development of competences in quality and lean practices, which may create competitive advantage.

This study contributes to the quality and lean literature and provides empirical evidence of the synergetic effects between investments in quality and lean practices. The analysis offers a greater understanding of the mechanisms that can be used to maximise the impact of investments in lean practices, from a global perspective. The findings are important to the advancement of theory in operations management, as it integrates three research streams: quality practices, lean practices and swift even flow research.