Search results

Process capability indices as an important kind of indices are intended to provide single‐number assessments of the inherent process capability to meet specification limits on quality characteristic(s) of interest. In this paper the condition for the application of process capability indices is analyzed. On the basis of process capability indices, dynamic process capability indices as a new kind of indices to show the current process capability are discussed and the condition for the application of dynamic process capability indices is exhibited. Comparison between process capability index and dynamic process capability index and comparison between D_p and D_pk are made and the conclusions provide the approach for process control. According to the requirement of process capability indices provided by customer, quality control based on process capability indices dynamic process capability indices is ciscussed.

Assert that capability indices quantify process improvement in a simple way and, when used correctly, provide relevant benchmarks. Considers it important that managers fully understand the power and limitations of this quality tool. Asserts the process is on target when Cp and Cpk are equal. Contends that the observed differences are due to sampling error and that any capability index is simply an estimate of an unknown value. Concludes that the measurement of process capability and the assessment on internal and external suppliers performance using indices, is now widespread. Despite any problems, process capability indices are preferable to many other measures of process or supplier performance.

When the process probability distribution is non‐normal or is unknown, the process mean and standard deviation may not properly describe the distribution’s shape. Consequently, the traditional process capability indices (PCI) C_p, C_pk, C_pm and C_pmk cannot express the actual process capability. This paper presents a procedure to construct lower confidence limits for PCIs when the process distribution is unknown. First, the order statistics are utilized to find the estimators of C_p, C_pk, C_pm and C_pmk. Bootstrap simulation method is then utilized to construct the lower confidence limits of PCIs, thereby allowing the process’s capability to be evaluated. A numerical example demonstrates the effectiveness of the proposed procedure.

The purpose of this paper is propose a methodology for monitoring industrial processes that cannot be stabilized, but are nevertheless capable.

The proposed procedure uses the C_P(u,v) family of capability indices proposed by Vännman (including the indices C_PK, C_PM, C_PMK) combined with one‐sided two‐out‐of‐three and three‐out‐of‐four run rules strategies.

This paper introduces a new strategy, where capability indices are monitored in place of the classical sample statistics like the mean, median, standard deviation or range.

When doing a capability analysis it is recommended to first check that the process is stable, e.g. by using control charts. However, there are occasions when a process cannot be stabilized, but is nevertheless capable. Then the classical control charts fail to efficiently monitor the process position and variability. The approach suggested in this paper overcomes this problem.

The experimental results presented in this paper demonstrate how the new proposed approach efficiently monitors capable processes by detecting decreases or increases of capability level.

Organizations invest in novel digital innovations to improve their business processes. These innovations, including Industry 4.0 technologies, enable full organizational integration with business process management (BPM), thereby requiring interorganizational relationship (IOR) capabilities. Many organizations lack knowledge about areas of interorganizational (IO) capability for integrating digital innovations into their value chains. They therefore have difficulty understanding that, as a socio-technical concept, digitalization surpasses the intraorganizational level and requires tools to develop mandatory IOR capabilities. The authors’ systematic literature review (SLR) explores these capabilities within the discipline of BPM. The purpose of this paper is to address this issue.

This SLR follows the standard methodology for structuring a broad research field. The authors assessed capabilities relevant to manufacturing organizations from 58 academic articles published between 2011 and 2021.

Building on existing firm-centric capability frameworks, the authors developed individual capabilities into a novel framework of digital interorganizational value chain (DIOVC). The authors’ conceptual model provides a basis for researchers and practitioners to consider capabilities and the theoretical spectrum of IO value chains.

Future studies should validate these DIOVC capabilities as input for an updated model of BPM maturity aimed at improving business process performance through digital innovations.

This study provides organizations with IOR knowledge, supports decision makers in governing digital innovations and develops IO capabilities to improve their value chain performance.

The authors’ DIOVC capability framework is robust, with constructs and dimensions grounded in the literature, demonstrating theoretical and practical relevance.

This paper aims to propose a conceptual framework to integrate a maturity model to the supply chain (SC) strategy, in order to understand how a maturity model can be useful in diagnosing and developing the capabilities of SC business processes (BPs) to meet SC's strategy.

The proposed framework was based on an SC strategy framework, in which a maturity model was added in order to diagnose and identify SC process capabilities that need to be developed, per maturity level, according to the type of SC strategy and the competitive strategy. A grid was proposed to analyze the relationship between them. An exploratory case study (multiple cases) was applied to verify the applicability of the model.

Findings indicate that a maturity model can delimit and align, as far as the company needs to reach, the SC strategic interests with the company's competitive objectives. However, some barriers and facilitating factors implicit can impact on this alignment. It is also noted that the maximum level of SC management (SCM) maturity may not be in the strategic interest of the company.

Due to the few empirical studies on the value of maturity models, this research contributes to the understanding of the usefulness of an SC process maturity model for the SC strategy. Moreover, the framework can show how a maturity model can serve as a parameter and guide to develop the capabilities of processes, resources and activities to meet the SC strategy and the reach of the competitive strategy.

The purpose of this paper is to introduce a modified MC_p by considering the effect of gauge measurement error on the multivariate process capability index.

In this paper, the effect of measurement system on the quality characteristics appears as coefficient matrix A which changes the variance‐covariance matrix of quality characteristics ∑, into A ∑. In this case, the authors investigate the properties of multivariate index and present adjusted confidence intervals and critical values for capability testing purpose of this index.

The results show that the simplicity of the obtained index, calculating the true process capability by using empirical process capability and also computing the critical value and power of the process capability testing is simpler in this modified approach.

The results presented in this paper would help practitioners to determine their actual process capability and see if their processes meet the preset capability requirement, and then make reliable decisions.

Based on the dynamic capability theory (DCT), this study examines the role of digitalisation vision and the impact of key information technology (IT) strategies, such as IT flexibility, IT integration and IT agility, on organisations' process innovation capability and the subsequent impact these may have on innovation performance.

Data for this study were collected from 153 public listed organisations in Malaysia. The survey questionnaire method was used to collect the data from the organisations' representatives.

Results showed that it is important for organisation to have a strategic digitalisation vision to improve their process innovation capabilities. IT agility and IT integration also had a significant positive relationship with the process innovation capabilities of the organisations, which in turn had a positive impact on innovation performance.

Digital transformation and innovation are crucial for organisations to survive in the era of Industry 4.0. However previous studies have not captured the role of digitalisation vision, strategic IT components and its impact on process innovation capabilities. The current study filled up the gap and examined these relationships. The outcome of this study provides valuable insights for managers to understand the importance of digitalisation and the need to focus on key IT strategies. Such insights can be used to improve organisations' process capability which is critical for innovation and performance.

In highly dynamic industries, business processes require exploitation, i.e. activities that are associated with an increase in productivity through automation, standardization, integrated architectures, and the usage of existing IT resources. As a complementary capability, exploration is needed, i.e. the ability to flexibly implement new and innovative IT resources (Lee et al., 2015). The purpose of this paper is to use the concept of ambidexterity, which is researched intensively outside the domain of business processes (e.g. Gibson and Birkinshaw, 2004; Tang and Rai, 2014), to address this paradoxical trade-off within business processes.

The paper follows a qualitative approach. A multiple case study comprising 11 interviews and additional document analysis in six organizations is conducted in the German energy sector to examine the proposed framework.

This paper shows the importance of balancing exploitative and explorative business process IT (BPIT) capabilities. The process-theoretical outcome of this study is the BPIT Capability Framework that provides explanation for the interaction between exploitation and exploration.

This study contributes to the understanding of how to build ambidextrous BPIT capabilities by explaining the underlying mechanisms for feedback loops that occur in cases of imbalance. The scope of the conducted study presents a limitation and thus future research is encouraged to further validate the findings of this paper.

By drilling down to the process level, this paper addresses the gaps that limited empirical studies have in business process management research (Recker and Mendling, 2015) and the focus on business processes that is lacking from the literature on organizational IT management (Gregory et al., 2015).

The current study aims to investigate the existing relationship between knowledge management (KM) infrastructures, KM process capabilities, creative organizational learning (OL) and organizational performance.

Statistical population includes executives of knowledge-based companies in Tehran Science and Technology Park of Iran. The 68 questionnaires were distributed among the census, of which 60 questionnaires were completed correctly. The research data were analyzed by SPSS and PLS software. The unit of analysis is a company that has adopted a knowledge management system (KMS). Target population of the research consisted of 85 top managers of knowledge-based companies in Tehran Science and Technology Park of Iran (N = 85). Random sampling method was applied in this study, and 71 top managers were considered as the statistical sample based on the “Morgan Table”. One standard five-point Likert questionnaire was adopted and distributed between top managers in the park; 62 questionnaires were returned, among which 60 were statistically investigated. The structural relations among variables were tested using the partial least squares method.

This study shows that the KM processes can mediate between creative OL and factors in the KM infrastructure. The results of the study demonstrate that KM process capabilities have the most crucial role in creative OL. The results indicate a significant influence of the infrastructure capabilities on the process capabilities, also the impacts of KM process capabilities on creative OL and the impacts of creative OL on organizational performance was confirmed.

Using a holistic view of the KM performance framework, this study has provided insights to KM for researchers because it explains the integrated aspects of KM performance by examining the relationships between the KM infrastructure, knowledge process capabilities, and organizational outcomes. Previous studies on KM have been fragmented because they only consider some aspects of KM performance rather than using a holistic view of the KM performance framework: they have examined the relationship between one or two facets of KM enablers and process capability, or between KM process capabilities and organizational performance.

In order to manage rapid change and global competition in business environments, knowledge workers should create new business opportunities and continuously question what and how they can contribute to these chances. Organizational KMS should support the learning processes of their knowledge workers.

The continuous learning and experiments are necessary in order to produce new ideas and products: it is critical to emphasize the importance of a KM infrastructure that supports and encourages learning in organizations. The creative learning in turn affects organizational performance indicating that without learning, organizations cannot overcome the boundary of old business practices and adjust to change in environments.

Previous researches did not appraise the effect of KM and its capabilities on organizational performance, and the specific influence of creative OL was disregarded. The present study demonstrates the mechanism of KM effect on organizational performance and describes the comprehensive dimensions of KM performance.