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The purpose of this paper is to theorise and develop seven dimensions (strategic supplier partnership, level of information sharing, quality of information sharing, customer service management, internal lean practices, postponement and total quality management) into a supply chain management (SCM) practices (SCMPs) construct and studies its causal relationship with the conceptualised constructs of supply chain performance (SCP) and manufacturing firms’ performance (MFP). The study also explores the causal relationship between SCP and MFP.

Data were collected through a survey questionnaire responded by 249 Jordanian manufacturing firms. The relationships proposed in the developed theoretical framework were represented through three hypotheses: H1 – there is a significant relationship between SCMPs and SCP; H2 – there is a significant relationship between SCMPs and MFP; and H3 – there is a significant relationship between SCP and MFP. Linear regression, ANOVA and Pearson correlation were used to test the hypotheses. The results were further validated using structural equation modelling.

The results indicate that SCMPs have a positive effect on SCP (H1), which in turn also positively affect MFP (H3). Despite this intermediary positive effect of SCMP on MFP through SCP, the study also suggests that SCMPs have a direct and positive effect on MFP (H2).

This study provides hard evidence indicating that higher levels of SCMPs can lead to enhanced supply chain and firms’ performance. It also provides SC managers of manufacturing firms with a multi-dimensional operational measure of the construct of SCMPs for assessing the comprehensiveness of the SCMPs of their firms.

This study is among the very first SCM researches conducted on the Jordanian manufacturing sector, particularly, in relation to the practices that manufacturing firms in this country need to adopt to make their supply chains a solid competitive vehicle for their development. The results have broader implications for all manufacturing companies, particularly in developing economies where the growth of manufacturing and the development of integrated supply chains are key stages in economic development.

Many companies are taking a process view as a result of business‐process re‐engineering exercises, statutory compliance (e.g. Securities and Futures Authority), reaction to market forces (e.g. to achieve accreditation under ISO9001:2000 or BS5750) and the promotion of integrated computer and information systems (e.g. computer integrated manufacture). This means questioning the way in which companies operate and has implications for management. Business process modelling (BPM) and business‐process simulation (BPS) help to facilitate process thinking. BPM provides management with a static structured approach to business improvement, providing a “holistic” perspective on how the business operates, and provides a means of documenting the business processes while BPS allows management to study the dynamics of the business and consider the effects of changes without risk. There are a number of BPM and BPS methodologies, approaches and tools available, each of which may be applicable to different circumstances. This paper briefly reviews the diverse literature in relation to manufacturing management. Evidence from the literature indicates that few tools are available for supporting manufacturing‐business‐process‐management and that, except for a few small‐scale processes, BPS implementations in manufacturing have had limited success. This paper identifies the reasons for this and suggests a practical way forward until hardware and software limitations are overcome.

Businesses face increasing competition in local, international and global markets where responsiveness to changes within these markets is the key to success and survival. Consequently business strategies need to be consistently re‐defined to effectively reflect the different requirements of customers and to respond to changes in the business environment. The process of generating strategies is not always a simple decision‐making task and revised business and corporate strategies are often generated without considering the structure of the business, particularly at operational level. Furthermore, there is considerable vagueness in the literature and in practice about what constitutes strategy management. This paper reviews the diverse literature in strategy management and presents a business process model of the strategy generation process to ensure consistent generation and communication of strategy throughout an organisation. The performance of a business strategy can then be measured against a model of initial alignment and effective implementation.

The purpose of this study was to investigate and propose the appropriate K‐mapping models as an approach to integrating key project components and technologies for the effective improvement of project performance within and across construction projects.

In this holistic, single‐case study, one of the largest construction consulting firms in South Korea has been studied by conducting 15 semi‐structured interviews and the different loci for each of the K‐mapping components are identified and analyzed. Based on the different loci, four types of the K‐mapping model are provided and elucidated.

Research findings indicate that these four types of the K‐mapping model provide the criteria to identify the appropriate types of K‐map for construction project organizations, according to the characteristics and conditions of their own construction personnel, construction processes, and K‐transfer technologies. With the K‐mapping models, an appropriate knowledge management system (KMS) can be developed more effectively.

First, as interpretivism was adopted as the research philosophy, the case study findings were subjective and qualitative to both the interviewees in the case study company and the researchers, though this study provided an important underpinning for future research on K‐mapping within construction project organizations. Second, the theory developed in this study was based on an investigation of the appropriate K‐mapping models with only a single case study. Nevertheless, this case study provided sufficient data and information to develop and propose a theory for successful K‐mapping model development within construction project organizations.

In the KM area, the definition, benefits, purposes, principles and types of K‐map have been already provided by many KM researchers and practitioners. However, no industry (practical)‐based K‐mapping model has been developed and proposed, especially in the construction industry. Accordingly, the originality of this study to be presented in one of the paper's conclusions: construction processes must be considered and adopted as a key component in the K‐mapping process, and the discussion of the four types of K‐map this research have generated, which significantly expands the existing literature on K‐mapping.

Reveals that the majority of those writing on the subject of managing quality in a service environment argue that this is more difficult than in manufacturing. Tries to redress this balance by presenting a number of reasoned arguments. The material presented is based heavily on opinion rather than fact, but intends to cause researchers and students alike to question some of the traditional arguments and perhaps even spark a debate on the topic which examines key features of manufacturing and examines the difficulties they present in relation to the management of quality. Concludes that while the management of quality in services is different to manufacturing, it is not always the case that it is more difficult.

This research is an effort to conceptualize the relationship between total quality management (TQM) and knowledge management in a new way. While some researchers considered knowledge management as a facilitator of TQM other scholars concerned TQM as an antecedent for knowledge management. The purpose of this paper is to propose a reciprocal causation between TQM and knowledge management.

The main focus of literature review is focusing on common practices of TQM and knowledge management. In the next step, joint variance analysis method is used to reanalyze the results of the empirical studies linking TQM to knowledge management. This approach aims to divide the multiple correlation squared and demonstrate what portion is distinctly connected to predictor variables and what portion is on account of common variance among predictors.

The result indicates that nearly half of all explained variances in empirical studies that considered the relationship between TQM and knowledge management disregarding the criteria are accounted for the joint variance of TQM and knowledge management processes. Therefore a reciprocal causation between TQM and knowledge management can be formulated.

This research is one of the first studies which explores the diverse results of the relationship between TQM and knowledge management from a methodological perspective.

Many organisations, particularly SMEs, are reluctant to invest time and money in models to support decision making. Such reluctance could be overcome if a model could be used for several purposes rather than using a traditional “single perspective” model. This requires the development of a “general enterprise model” (GEM), which can be applied to a wide range of problem domains with unlimited scope. Current enterprise modelling frameworks only deal effectively with non‐dynamic modelling issues whilst dynamic modelling issues have traditionally only been addressed at the operational level. Although the majority of research in this area relates to manufacturing companies, the framework for a GEM must be equally applicable to service and public sector organisations. This paper identifies five key design issues that need to be considered when constructing a GEM. A framework for such a GEM is presented based on a “plug and play” methodology and demonstrated by a simple case study.

Delivering premium services and quality products are critical strategies for success in manufacturing. Continuous improvement (CI), as an underlying foundation for quality management, is an ongoing effort allowing manufacturing companies to see beyond the present to create a bright future. We propose a novel integrated fuzzy framework for analyzing the barriers to the implementation of CI in manufacturing companies.

We use the fuzzy failure mode and effect analysis (FMEA) and a fuzzy Shannon's entropy to identify and weigh the most significant barriers. We then use fuzzy multi-objective optimization based on ratio analysis (MOORA), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy simple additive weighting (SAW) methods for prioritizing and ranking the barriers with each method. Finally, we aggregate these results with Copeland's method and extract the main CI implementation barriers in manufacturing.

We show “low cooperation and integration of the team in CI activities” is the most important barrier in CI implementation. Other important barriers are “limited management support in CI activities,” “low employee involvement in CI activities,” “weak communication system in the organization,” and “lack of knowledge in the organization to implement CI projects.”

We initially identify the barriers to the implementation of CI through rigorous literature review and then apply a unique integrated fuzzy approach to identify the most important barriers based on the opinions of industry experts and academics.

This paper responds to calls from the literature for research identifying the difference between the effect of internal agents and external agents, such as customers, suppliers and government on sustainable supply chain management (SSCM). The paper also determines whether there is a dynamic or interactive relationship between the two types of agents.

Activity theory was used as the theoretical framework for understanding how internal and external agents affected both SSCM motivation and facilitation and possible interactions between the two. A cluster analysis identified how internal and external agents affected SSCM initiatives, interactions, the conditions under which this occurs and the mechanisms of this effect.

Internal and external agents differ in the type, sequence and diversity of their effect on SSCM. While external agents had both an SSCM motivating and facilitation effect, internal agents only had a facilitating effect. Customers were only a significant SSCM motivation in 35% of the cases. Government regulations had a dynamic effect, changing from motivation to facilitation as the SSCM initiative developed. External agent SSCM motivation and facilitation were more internalized in organizations which were more internationally oriented.

Local institutional frameworks motivate and facilitate SSCM initiatives, while head office initiatives and international best practice agencies encourage an integrated combination of external agent motivation and facilitation and internal facilitation.

The findings extend the SSCM literature by identifying the processes of agent SSCM motivation and facilitation, the dynamic nature of agent SSCM effects and the mechanism through which externally motivated and facilitated SSCM becomes internalized.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.