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The purpose of this study is to examine the mediating role of manufacturing flexibility in the relationship between knowledge creation, technological turbulence and performance. In an increasingly competitive and changing environment, firms need to boost their technological and management know-how to adequately develop manufacturing flexibility.

This study analyzes survey data collected from 370 manufacturing firms. Validity and reliability analyses were conducted using SPSS and Amos. The research hypotheses were tested using covariance-based structural equation modelling.

The main findings show that knowledge creation positively and significantly affects business and operational performances directly, and indirectly, through manufacturing flexibility. Moreover, technological turbulence has a positive and significant effect on it. This finding contributes to understanding why some firms get better outcomes from manufacturing flexibility than others, a disputed issue in the literature.

This study highlights the need for manufacturing firms to foster cultures of knowledge creation, to better educate and train employees and to develop other instruments of knowledge creation.

This study makes several contributions to manufacturing flexibility literature: (1) establishing a link between technological turbulence and knowledge creation to develop manufacturing flexibility; (2) add empirical evidence on the relation between manufacturing flexibility and performance and (3) contributes to consolidating the mediation role of manufacturing flexibility in the relations between knowledge creation and business performance, as studies focussing on such a role are scarce in the literature.

The purpose of this paper is to explore different drivers and volume flexibility strategies employed in manufacturing firms. It also examines contingent factors, which determine volume flexibility requirement in manufacturing firms.

Using a multi-case study approach, the study examines and analyses drivers, strategies and contingent factors that affect volume flexibility in four Indian manufacturing plants belonging to automobiles, auto ancillary, fashion apparel and electrical industry.

The empirical analysis suggests various drivers of volume flexibility and different strategies employed by firms to enhance flexibility. The study also illustrates various contingent factors that determine the need of volume flexibility in firms.

The sample of the study is majorly confined to the northern region of India. Methodologically, the analysis is solely based on the qualitative data.

The study suggests practitioners to consider a range of contingent factors, while evaluating the need of volume flexibility in manufacturing plants. Rather than relying on a single strategy, a mix of strategies should be used to develop volume flexibility in firms.

The identification of a range of strategies employed by volume flexible firms as well as contingent factors that need to be evaluated before employing volume flexibility are the major contributions of this study.

The purpose of this paper is to study the effect of technology adoption on operational competitiveness by taking an example from international manufacturing companies.

This paper develops a conceptual model to generate strategic flexibility and benefit for a manufacturing firm by managing manufacturing strategy and technology adoption with different leadership roles.

The results show that the leadership role is a significant factor to motivate strategic flexibility and generate higher benefit. For intellectuals, the mechanism provides a new approach to explicate technology adoption in a manufacturing company. Besides, it provides a deep‐rooted preliminary point for supplementary empirical assessment. The mechanism facilitates managers to expand their understanding of the leadership role for trust building and knowledge sharing in manufacturing firms.

With that enhanced understanding, the managers can spotlight their actions, which help further to perk up their firm's competitiveness provoked by supporting the knowledge sharing activities through appropriate leadership roles.

The mechanism developed in this study is believed to be the first sober effort to provide a deeper theoretical understanding of trust building for improving operational competitiveness in manufacturing firms with a practical approach.

This paper, originally published in 1987, seeks to outline an agenda for conducting rigorous research into the flexibility of manufacturing processes.

An initial domain for defining flexibility is established, specific measures are suggested, and sampling issues are discussed. There is also a discussion of relevant research problems that can be addressed once valid and reliable operationalisations exist.

Its underlying premise is that current efforts are being impeded by the absence of operational measures for the concept.

A useful historical perspective on manufacturing processes.

The study aims to conceptualize and empirically develop an instrument to measure manufacturing flexibility development practices in firms.

Using a dataset of 315 responses, a series of procedures were used to develop, modify and refine item measures of constructs to enhance their reliability and validity. Further, following a competing model strategy, alternative models were compared to finalize the manufacturing flexibility development practices.

The study develops 36-item instrument capturing eight distinct constructs that influence manufacturing flexibility development, namely operational improvement practices, supplier integration practices, advanced manufacturing technologies, advanced human resource practices, supplier flexibility, customer integration practices, marketing and manufacturing integration practices and product-process technology integration. The derived factors exhibit an adequate level of consistency, reliability and validity.

Since the external environment is always affected by externalities, tools and technologies used to develop flexibility may also vary over time. Therefore, the developed measurement instrument can be used over the medium term. Further, the statistical generalizability of this study cannot be drawn beyond the scope of this sample.

The derived items measure and their underlying factor structure facilitates practitioners to identify areas that need attention. Practically, practitioners should strive to improve multiple factors that influence manufacturing flexibility to arrive at the full realization of flexibility.

This study is probably the first to develop an instrument for assessing the factors influencing the potential of manufacturing flexibility.

Entrepreneurial orientation (EO) purportedly enhances a firm's competitive edge, but its alignment with specific dimensions of manufacturing flexibility has not been convincingly documented. The purpose of this study is to investigate the effects of several identifiable aspects of EO on particular types of manufacturing flexibility.

Using the data collected from 115 motherboard manufacturers, the study employs multiple regression analysis to examine the effects of entrepreneurial practices on manufacturing flexibility.

The statistical results lead to the following conclusions: autonomy, innovativeness, risk‐taking and proactiveness have significant positive effects on new product flexibility; autonomy, innovativeness, and competitive aggressiveness improve product mix flexibility; innovativeness, proactiveness, and competitive aggressiveness determine volume flexibility.

The research focuses exclusively on external manufacturing flexibility, ignoring, for the time being, internal manufacturing flexibility factors.

The outcomes of the present study reveal that manufacturing flexibility cannot be achieved by simply installing a computer‐aided system; rather, it needs to be planned, managed, and integrated with a firm's entrepreneurial endeavors.

This is the first empirical study to investigate the effects of EO on manufacturing flexibility rather than on business performance, which most of the previous research on this topic has emphasized. In terms of practical applicability, the findings provide plant managers with valuable guidelines for improving manufacturing flexibility by undertaking appropriate entrepreneurial action.

Manufacturing industry is under pressure to improve productivity and reducing costs through minimization of wastage of resources. This paper aims to present case study of an automobile component manufacturing company to implement lean manufacturing through resource flexibility and also demonstrate the various areas of future scope for improving lean manufacturing.

The case study has been conducted using the flexible system methodology framework. For measuring resource (labor and machine) flexibility and lean manufacturing, various parameters contributing towards labor flexibility, machine flexibility and lean manufacturing are identified. To determine their relative weights, analytical hierarchy process has been employed. A specially designed questionnaire is used to collect the information during case study on different aspects of resource flexibility and lean manufacturing. SAP-LAP analysis has also been carried out, to look into the ways the company is building up resource flexibility and lean manufacturing.

Although all parameters of labor flexibility contribute towards overall labor flexibility but ability of workers to work on different machines has the maximum impact of 35.16 percent. Ability of machines to perform diverse set of operations has maximum contribution of 40.38 percent towards machine flexibility. Similarly elimination of waste is 35.15 percent responsible for lean manufacturing implementation. There is also a huge scope to achieve higher degree of lean manufacturing by implementing zero defects, changing attitude towards change and installing flexible machines. It is inferred that 76.2 percent of lean manufacturing is endorsed by resource flexibility.

The present study includes only labor and machines as the elements of resource flexibility. Other resources may also be included to compute overall resource flexibility.

The present study provides guidelines to assess the status of resource flexibility and lean manufacturing. According to conclusions, feeble areas in the manufacturing system can be identified and a suitable course of action might be planned for the improvement. Hopefully this study will help the firm's management to identify the problems to manage resource flexibility and implement an effective lean manufacturing.

In this work, the theoretical perspective has been used not only to update the original instrument, but also to study the subject from a perspective beyond that usually associated with resource flexibility and lean manufacturing.

The purpose of this paper is to propose a novel integrated approach using analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods for evaluation and prioritization of appropriate manufacturing flexibility type required in the face of multiple environmental uncertainties.

Using a case study of an Indian fashion apparel firm, the study demonstrates the application of the proposed integrated framework for evaluation and prioritization of manufacturing flexibility. The study uses AHP method to determine importance weight of environmental uncertainty criteria and subcriteria and then employs TOPSIS method to determine the final ranking of manufacturing flexibility types required to cope up with these uncertainties.

The findings of the case suggest that the proposed integrated approach is feasible and practically implementable for manufacturing flexibility assessment.

AHP has been extensively studied and used, but the major limitation of this proposed approach is the involvement of large number of pairwise comparisons leading to difficulty in maintaining consistency in pairwise comparisons.

The proposed approach can work as a benchmarking tool to practitioners in evaluating and prioritizing manufacturing flexibility alternatives and to suggest strategic allocation of resource by prioritizing different manufacturing flexibilities types.

Unlike conventional approaches, the study provides meaningful knowledge to decision makers by demonstrating a simple, flexible, and efficient method to evaluate and rank the appropriate manufacturing flexibility types.

This paper focuses on understanding the contribution of Industry 4.0 technologies to manufacturing flexibility.

A multiple-case study was conducted through interviews and complementary data from 12 adopters of Industry 4.0 technologies from the industrial sector. To enable a broad perspective, cases from 5 industry sectors with different technological intensity levels were studied.

The findings show that Industry 4.0 technologies are mostly used to improve machine flexibility since there is a major focus on technological approaches rather than on wider flexibility. The results also showed that cloud services, IoT, and data analytics provide the basis for flexible operation, and collaborative robots, ERP/MES/PLM, AGVs, and traceability devices are the most commonly implemented technologies for flexibility. However, inherent contingency factors such as production complexity and product life cycle need to be considered.

This article expands the research on manufacturing flexibility, considering new capabilities introduced by Industry 4.0.

The objective of this paper is to empirically test and verify the enablers of volume flexibility and product-mix flexibility and to assess the influence of these flexibilities on operational performance.

A research framework consisting of nine pairs of hypotheses was developed using an extensive literature review. Using a self-administered questionnaire, 391 responses were collected, and these responses were analyzed using descriptive statistics, factor analysis, and structural equation modeling techniques.

The findings empirically confirm the enablers of volume flexibility and product-mix flexibility. The proposed model explained 59 percent variance in volume flexibility and 63 percent variance in product-mix flexibility. Volume flexibility and product-mix flexibility together explained 38 percent variance in operational performance.

Theoretically, this study advances flexibility literature in two significant ways. First, the study conducts first of its kind quantitative empirical investigation considering upstream, downstream, and internal integration practices as enablers of volume flexibility and product-mix flexibility. Second, this study adds to the flexibility literature by suggesting the positive influence of volume and product-mix flexibility on the operational performance of firms.

The study reinforces the role of enablers in the development of volume and product-mix flexibilities. Thus, the study provides a comprehensive view of flexibility enablers that can be used as a diagnostic tool, which practitioners can use to assess and deploy flexibility.