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The result of a Teaching Company Scheme between the University of Newcastle‐upon‐Tyne and Eaton Ltd (axle division), Newton Aycliffe, is presented. The programme was devel‐.pb oped to address quality problems encountered in the manufacture of the main driving gears in truck axles. There had been quality‐related rejections of gearsets in the plant and by customers. The nature of the problems was essentially unknown; it was generally termed “distortion” and was thought to be related to the heat treatment process. The approach to quality appraisal in two areas of the plant is described and a description of the production environment is outlined. The use of quality procedures and reporting systems for quantitative analysis is developed. Among the major findings are: the need for communication; the important role of simple quality systems; the need to identify material quality and process‐induced variables.

With support from the dynamic capabilities theory, this paper examines the role of Cloud Computing technology use in logistics (Cloud-Supported Logistics) and its effect on business results in Lean manufacturing management (Lean Production implementation) and Supply Chain Integration contexts.

Using the survey method, a random sample of 260 companies in intermediate positions in their supply chains was gathered from a population of 1,717 Spanish companies and used to test five hypotheses. The data were collected by telephone survey using a computerised system with a response rate of 15.6% (260 valid questionnaires). Structural equation modelling was used to test the five proposed hypotheses.

The findings indicate that Cloud-Supported Logistics use plays an important role in achieving better business results in Lean Production environments. Lean Production has been found to have both a direct effect and an even more powerful indirect effect on performance through the Cloud-Supported Logistics and Supply Chain Integration that these technologies produce. Supply Chain Integration is also found to have a mediating effect in the Cloud-Supported Logistics–performance relationship.

This study is valuable for academics and practitioners as it provides evidence of the relevant role played by Cloud-Supported Logistics in Lean Production implementation contexts. Cloud-Supported Logistics and Lean Production are strategically and operationally linked and their joint use results in Supply Chain Integration and better business performance.

The purpose of this paper is to review past and current research on the productivity problems and how to alleviate it by appropriate training.

The article presents the collective results of two experiments, a grocery store chain, and a top outsourcing provider to show the higher levels of productivity can be achieved by proper training methods.

The results of two experiments specify that businesses should incorporate proper training techniques in order to increase their productivity. If such an approach to generating high levels of productivity contingent on training is implemented, we expect that business should harvest the benefits.

Ideally, the experiments reported on should be extended to comprise a measure of the amount of employer‐provided on‐the‐job training and training costs.

This research contributes to the current training and productivity literature by emphasizing, to both human resource practitioners and policy makers, inadequate investment in workforce training is related directly to poor employee. The results have offered practical implication to organizational training.

The customer enquiry management (CEM) process is of strategic importance in engineer‐to‐order contexts but existing literature does not adequately describe how firms support delivery date setting and order acceptance decisions in practice. This paper seeks to explore how and why the CEM process varies between companies in the capital goods sector, thereby taking a contingency theory approach.

Multi‐case study research involving 18 Italian capital goods manufacturers in four industrial sectors. Face‐to‐face interviews with senior representatives have been conducted. Companies have been grouped into five clusters, based on similarities in their CEM decision‐making modes, to aid analysis.

Three contingency factors were found to be particularly relevant in determining CEM modes: degree of product customization, flexibility of the production system, and uncertainty of the context. These factors affect the choice of specific CEM decision‐making modes. However, a high level of cross‐functional coordination and formalization of the process were found to constitute best practices whatever the contingency factors.

The research focuses on companies belonging to the Italian capital goods sector – findings may differ in other countries and sectors.

The results indicate that all firms, including small and medium‐sized companies, should implement high levels of cross‐functional coordination and formalization in their CEM practices, in order to improve their performance. For other aspects of the CEM process, including supplier and subcontractor monitoring, the company context will indicate whether these aspects are required, according to a need of matching the approach to CEM with specific sets of contingency factors.

This paper provides a rare insight into the CEM processes found in practice.

The purpose of this paper is (1) to review, analyze and assess the existing literature on lean tools selection studies published from 2005 to 2021; (2) to identify the limitations faced by previous studies; and (3) to suggest future works that are necessary to facilitate the selection of lean tools.

A systematic approach was used in order to identify, collect and select the articles. Several keywords related to the selection of lean tools were used to collect articles from different Scopus indexed journals. Next, the study systematically reviewed and analyzed the selected papers to identify the lean tools' selection method and discussed its features and limitations.

An analysis of the results showed that previous studies have adopted two types of methods for selecting lean tools. First, there are various traditional methods being used. Second, multi-criteria decision-making (MCDM) methods were commonly used in previous studies, such as the multi-objective decision-making method (MODM), single multi-attribute decision-making (MADM) methods and hybrid (MCDM). Moreover, the study revealed that the lean tools' selection methods in previous studies were based on evaluating the relationship between either lean tools and performance metrics or lean tools and waste, or both.

In terms of its theoretical value, the study is considered as an extension of the previous researches performed on this topic by determining and analyzing the features of the most selection methods of lean tools. Unlike previous review papers, this review had considered discussing and analyzing the characteristics and limitations of these methods. Section 2.2 of this paper reviewed some of the categories of MCDM methods as well as some of the traditional methods used in the selected previous studies. Section 2.1 of this paper explained the concept of lean management and its application benefits. Further, only three sectors were covered by the previous studies in this review paper. This study also provided recommendations for future research. Therefore, it provided researchers with a good conception of how to conduct the studies on lean tools selection. Besides, knowing the methods used in previous studies can help researchers develop new methods to select the best set of lean tools. That is, this study provided and advanced the existing knowledge base for researchers concerning lean tools selection, especially there is limited availability of review papers on this topic. Moreover, the study showed researchers the importance of the relationship between lean tools and indicators or/and performance indicators to determine the appropriate set of lean tools so that the results of future studies will be more realistic and acceptable.

Practically, manufacturers face a significant challenge when selecting proper lean tools. This study may enhance managers, manufacturers and company's knowledge to identify most of the methods used to choose the best set of lean tools and what are the advantages, disadvantages and limitations of these methods as well as the latest studies that have been adopted in this topic. That means this study can direct companies to prioritize the application of lean tools depending on either the manufacturing performance metrics or/and manufacturing wastes so that they avoid incorrect application of lean tools, which will add more non-value added activities to operations. Therefore companies can decrease the time and cost losses and enhancing the quality and efficiency of the performance. Correctly implementing the best set of lean tools in companies will lead in general to correctly applying lean management in corporations. Therefore, these lean tools can boost the economic aspect of companies and society through reducing waste, improving performance indicators, preserving time and cost, achieving quality, efficiency, competitiveness, boosting employee income and improving the gross domestic product. The correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. Besides, the correct lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right selection of lean tools will have positive effects on both the environment and society. The study may also encourage manufacturers and researchers to adopt studies on lean tools selection in small- and medium-sized companies because the study referred to the importance and participation of these kinds of companies in a large proportion of the economy of developing countries. Further, the study may encourage some countries that have not previously adopted this type of study, academically and industrially to conduct lean tools selection studies.

As mentioned previously, the correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. The proper lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right choice of lean tools will positively affect both the environment and society.

The study expanded the efforts of previous studies concerning lean management features. It provided an accurate review of most lean tools selection studies published from 2005 to 2021 and was not limited to the manufacturing sector. It further identified and briefly described the selection methods concerning lean tools adopted in each paper.

The purpose of this paper is to evaluate the European Regions for Innovative Productivity project that established Innovative Productivity Centres (IPCs) to assist SMEs in the North Sea Region of Europe to develop a process improvement capability. A conceptual framework explains how a process improvement methodology developed for large firms was adapted and shaped to meet the needs of SMEs.

A comparative case study of 23 SMEs within six European countries. A protocol was developed to collect financial and operational data. This was supplemented by observations, secondary data and field notes. An established research model was used to evaluate the effectiveness and impact of the process improvement interventions.

The intervention context and structure of the IPCs varied by country which shaped process improvement interventions at two levels: the country and the firm. During diffusion three process improvement variants emerged that were tailored to fit the local context. Developing a process improvement capability depended upon the availability of company resources, establishing KPIs and change agent support.

The research contributes to knowledge and theory on diffusion and institutionalization by examining how SMEs responded to institutional pressures by implementing process improvement practices in different ways. Heterogeneity of both the IPCs and the external change agents were the drivers in shaping the improvement practices.

This paper aims to propose a model of production management that integrates knowledge management, as a third dimension, to the production and work dimensions and to identify factors that promote a favorable context for knowledge sharing and results achievement in the production operations shop floor environment.

The model proposed is built from opportunities identified in the literature review.

The factors in the model integrate its three main components: knowledge management, production organization and work organization, providing a representation of the dynamics of the workplace and shop floor environment.

The proposed model and its factors allow managers to better understand and to improve the organization activities, because it integrates knowledge management with the production organization and work organization components of traditional models.

Literature acknowledges the role of knowledge as competitive advantage, but it is still dealt in an implicit way within the traditional models of production management. This paper proposes a model and factors that provide a favorable context for tacit knowledge sharing and results achievement in the production operations shop floor environment. The model explicitly integrates knowledge management with traditional models' components.

This study aims to improve productivity and customer satisfaction through lean manufacturing for metals and engineering industries. Its aims also to understand the concept of lean manufacturing, various tools and techniques of lean, lean implementation benefits and barrier toward its implementation. Then, on the basis of the result, a conceptual frame work was developed to reduce the existing gaps.

Lean thinking is one of the methods that can bring productivity and customer’s demand improvement for manufacturing and service giving industries. To arrive at the lean thinking productivity improvement and customer satisfaction of the sector (MEIs), intensive literature review and secondary data investigation were conducted.

Articles and secondary data related to the case were reviewed and found the existing gaps. The gaps identified such as missing energy waste, space waste and material waste, waste of knowledge or talents. In addition to the 5 S of kaizen, this study added safety as the sixth on the existing Kaizen’s strategies. In lean practice, managers give priority to waste reduction and ignore the product quality aspect, which lead to dissatisfaction among customers. Fragmented implementation of lean manufacturing and the conflict between human resource waste and unemployment were reconciled in this study. A model that can improve productivity and increase customer satisfaction was developed. Solutions to alleviate the problems and speed up development were forwarded.

This study focused solely on the manufacturing industries of developing countries, specifically deals with basic metals and engineering industries. In addition to this, the research didn’t take a case study on a specific firm as it is a literature review.

The findings of this study emphasized that lean manufacturing is the key for wise resource utilization, which enables a firm for cost, lead time and waste reductions on one hand and productivity and flexibility improvements on the other. To the end, lean can bring sustainable development and bright images to firms, and wellbeing life to workers together with customer satisfaction.

The gaps that have not been identified by other researchers were clearly discussed, and on the basis of the gaps, a new conceptual model was developed. This is useful to basic metals and engineering industries in overcoming resource-limitation problems by eliminating wastes.

The nature of evaluation research vis‐à‐vis management education and development (MED) has undergone major changes over the last 30 years. Broadly, the quantitative positivistic research designs of the early 1960s have given way to qualitative naturalistic designs. This shift represents a sea‐change both in terms of methodology employed by evaluation researchers in this field, and in terms of what is meant by evaluation.

The purpose of this paper is to develop a measurement framework to evaluate the lean readiness level (LRL) and lean systems (LS) within Kuwaiti small and medium‐sized manufacturing industries (K‐SMMIs). A measurement framework which encompasses the quality practices related to LS (processes; planning and control; human resources; top management and leadership; customer relations; and supplier relations) is used to assess the quality practices in K‐SMMIs and determine whether they have the foundation to implement LS.

The authors conducted a comprehensive literature review, semi‐structured interviews with 27 senior managers, and a quantitative survey administered to 50 K‐SMMIs. The responses were entered into SPSS software to conduct a reliability test and independent sample t‐test.

The results indicate that current quality practices within K‐SMMIs are not very supportive towards LS. Many factors are revealed to affect K‐SMMIs with respect to LS, including language barriers, and deficiencies in aspects including quality workers in terms of education and skills; technology; government attention; know‐how regarding LS; market competitiveness; and urgency for adopting LS.

Very limited information is available on LS and QI in Kuwait. The LRL framework should be tested in small and medium‐sized manufacturing industries (SMMIs) that successfully use LS, in order to provide a benchmark. The study's findings can be used as an internal checklist prior to and during lean implementation.

This LS and LRL measurement framework relating to K‐SMMIs represents a unique effort in the area of lean management.