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The literature highlights the relevance of performance measurement and management system in small and medium enterprises (SMEs) to face the current competitive environment. However, a number of studies investigate how performance measurement and management system is effective for evolving and how contingency factors could influence this change. Newer experiences are sporadic and rarely investigated by researchers and practitioners. The purpose of this study is to identify the feasible evolutionary path of performance measurement and management system in leading SMEs to respond to current business challenges. Furthermore, it aims to contribute to the understanding of the role of key contingency factors influencing this evolution.

A longitudinal case study, based on retrospective and real-time investigations, is performed to investigate the primary evolutions of the performance measurement and management system and its key determinants.

The findings highlight two evolution paths, increasing the maturity of performance measurement. The first path highlights a strong command and control of performance management; the second path shows a democratic and participative of performance management. Moreover, management information system, organizational culture and management style are highlighted as key contingency factors in the change of performance management.

The authors contribute to knowledge in performance measurement field, showing how the efforts for developing performance measurement and management system in a leading SME could determine two different evolutionary paths. Furthermore, the paper describes the increasing role of organizational culture, management style and management information system in performance management evolution, as well as the relevance of online chats and social media in performance management activities.

The purpose of the study is to test if it, by the use of a survey methodology, is possible to measure managers' awareness on, and specifically if there exist preconceived beliefs on, overall equipment effectiveness (OEE) results. The paper presents the design of the survey methodology as well as a test of the survey in one case company.

Actual OEE logs from a case company are collected and a survey on the data is designed and managers at the same case company are asked to answer the survey. The survey results are followed-up by an interview study in order to get deeper insights to both the results of the survey as well as the OEE strategy at the case company.

The findings show that the managers at this particular case company, on a general level, does not suffer too much from preconceived beliefs. However, it is clear that the managers have a preconceived belief that lack of material is logged as a loss much more often than what it actually is.

The test has only been performed with data from one case company within the automotive manufacturing industry and only the managers at that case company has been active in the test.

The survey methodology can be replicated and used by other companies to find out how aware their employees are on their OEE results and if possible preconceived beliefs exists.

To the authors' knowledge, this is the first attempt at measuring if preconceived beliefs on OEE results exist.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

A common understanding of what events to regard as production disturbances (PD) are essential for effective handling of PDs. Therefore, the purpose of this paper is to answer the two questions: how are individuals with production or maintenance management positions in industry classifying different PD factors? Which factors are being measured and registered as PDs in the companies monitoring systems?

A longitudinal approach using a repeated cross-sectional survey design was adopted. Empirical data were collected from 80 companies in 2001 using a paper-based questionnaire, and from 71 companies in 2014 using a web-based questionnaire.

A diverging view of 21 proposed PD factors is found between respondents in manufacturing industry, and there is also a lack of correspondence with existing literature. In particular, planned events are not classified and registered to the same extent as downtime losses. Moreover, the respondents are often prone to classify factors as PDs compared to what is actually registered. This diverging view has been consistent for over a decade, and hinders companies to develop systematic and effective strategies for handling of PDs.

There has been no in-depth investigation, especially not from a longitudinal perspective, of the personal interpretation of PDs from people who play a central role in achieving high reliability of production systems.

The purpose of this research is to discover equipment losses and assess the accomplishment of overall equipment effectiveness (OEE) values.

Industries specialized in die shops often have issues regarding their efficiencies, conferring to statistics further production line department procedure for various machines frequently suffered restrictions owing to excessive downtime and speed losses in machines thus, reducing their effectiveness and efficiency. OEE is a means of determining how effective a piece of equipment is when in working condition. Calculation of OEE finds the heart of the issue and the root cause for the underlying problem.

The dimensional outcomes suggest that the average machine effectiveness has not attained the norm of >85%, but there is still room for progression.

One recommended procedure to reduce losses is to keep the actual pace of operation and downtime of equipment constant. Many such suggestions are provided to reduce the losses.

The purpose of this study is to ensure productive, robust and sustainable production systems and realise digitalised manufacturing trough implementation of Smart Maintenance – “an organizational design for managing maintenance of manufacturing plants in environments with pervasive digital technologies”. This paper aims to support industry practitioners in selecting performance indicators (PIs) to measure the effects of Smart Maintenance, and thus facilitate its implementation.

Intercoder reliability and negotiated agreement were used to analyse 170 maintenance PIs. The PIs were structurally categorised according to the anticipated effects of Smart Maintenance.

Companies need to revise their set of PIs when changing manufacturing and/or maintenance strategy (e.g. reshape the maintenance organisation towards Smart Maintenance). This paper suggests 13 categories of PIs to facilitate the selection of PIs for Smart Maintenance. The categories are based on 170 PIs, which were analysed according to the anticipated effects of Smart Maintenance.

The 13 suggested categories bring clarity to the measuring potential of the PIs and their relation to the Smart Maintenance concept. Thereby, this paper serves as a guide for industry practitioners to select PIs for measuring the effects of Smart Maintenance.

This is the first study evaluating how maintenance PIs measure the anticipated effects of maintenance in digitalised manufacturing. The methods intercoder reliability and negotiated agreement were used to ensure the trustworthiness of the categorisation of PIs. Such methods are rare in maintenance research.

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

This paper presents the concerns in manufacturing supply chain. Further this study investigates the role of information technology (IT) and information sharing (IS) in manufacturing supply chain and determines its impact towards supply chain integration (SCI), supply chain performance (SCP), and manufacturing firm performance (FP) in Malaysia. The theoretical framework was proposed for the study on the basis of existing literature. The study administered a survey questionnaire to collect data from manufacturing firms in Malaysia with 112 respondents. A multiple regression analysis is conducted to establish the relationship between IT, IS, SCI, and FP. The study finds that IT and sharing has significant positive effect towards and performance. Firms that use IT and practice IS across partners in the supply chain are more likely to integrate their internal and external value chain for better performance both within and across the manufacturing firms in the supply chain. This study can be of interest to the manufacturing industry as well as other industry practitioners interested in improving the performance of the organization and supply chain in total. For supply chain practitioners, this results indicate that the firms should adopt IT and IS practices to strategically improve SCI. This in turn will also improve the supply chain network and firm’s performance. This study employs a newly developed framework which depicts the causal relationship between IT, IS, SCI, Supply Chain Performance, and FP in Malaysia. Furthermore, it closes a gap in existing literature by examining the effect IT and communication (ICT) practices toward manufacturing firms’ performance and SCP in a single setting. In addition, the current study attempted to construct a model which would estimate and interpret SCP and FP simultaneously, and to evaluate this model in an empirical fashion.

This paper aims to evaluate the usefulness of two conceptual frameworks: levers of control (LOC) (Simons, 1995) and performance management systems (PMSs) (Ferreira and Otley, 2009) for studying PM practices using a case study.

A case study method is used whereby data are collected through semi-structured interviews, examination of the group’s annual reports and internal documents.

A key finding of this study is the use of a PMS at the case company which is formally structured and with objectives, mechanisms and processes designed beyond a mere “performance measurement system.” While the case analysis indicates that most of the key components of the two frameworks are featured in the company’s PMS design, the uses of Simons’ (1995) LOC, however, are not consistent with the notion of “balance” as advocated by the model.

The evidence presented in this study is based on one large manufacturing company, and hence the findings cannot be generalized.

The findings of this study can be used in enriching the design of current proposed theoretical frameworks and also in encouraging management accounting researchers to continue the efforts of studying performance management (PM) practices.

A deeper understanding of PM practices using holistic frameworks has yet to receive more contested efforts from management accounting researchers. This paper attempts to contribute to this endeavor and fill in the gap in this area of research.

Logistics and supply chain management has been elevated to a strategic level whereby firms can simultaneously achieve differentiation and low cost for sustained competitive advantage. Empirical studies have often concentrated on logistics management in developed Western countries, displaying a bias towards the USA. This study applies the competency approach to explore logistics in Taiwan. A survey of 1,200 manufacturing firms was undertaken in order to examine the relationships between logistics competency, logistics performance, and financial performance, using exploratory factor analysis and the structural equation modelling technique. Four logistics competencies, namely, integration and knowledge competency, customer focused logistics competency, measurement competency, and agility competency were identified. The research findings revealed that (1) logistics competency was significantly related to logistics performance but not significantly associated with financial performance, and (2) logistics performance was positively associated with financial performance. These findings also implied that logistics competency has an indirect effect on financial performance through logistics performance. This finding confirmed the “world-class” logistics competencies (i.e. positioning, integration, agility, and measurement) as identified by MSUGLRT (1995). In addition, it suggests that logistics competency in a huge geographic area such as America can have the same effect in a smaller geographic area such as Taiwan.