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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.

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.

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.

This study aims to investigate digitalization as a performance driver in supply chains, especially the role of data analytics in the digitalization of procurement. The study investigates how digital procurement capabilities are linked to data analytics capabilities and supply chain operational performance and how this links to business success.

Using operational and dynamic capabilities as foundations for data analytics capabilities, this paper studied the digital procurement capabilities and proposed the conceptual model and hypotheses for empirical testing. The collected industry survey data and structural equation method are then applied to test the hypotheses.

The study confirms positive and significant relationships among digital procurement capabilities, data analytics capabilities and supply chain performance. Digital procurement capabilities mediate the positive relationship between external data analytics capabilities and supply chain performance.

This study has some limitations that should be addressed. The empirical study was based on survey data from a questionnaire that was probably challenging for some respondent companies with low levels of digital procurement and data analytics. Also, it is necessary to adopt secondary data to measure business performance in future studies which reduces the effect of subjective bias.

From the managerial point of view, the findings highlight the importance of gaining knowledge from gathered data and digitalized processes. Managers must focus on data utilization capabilities to improve the operational performance expected from the digitalization of supply chain activities. In addition, managers need to consider exploiting of data through new creative approaches as part of standardized operations.

The present study contributes to existing knowledge by investigating the mediating role of data analytics capabilities between the digitalization of procurement and supply chain performance. The findings support a positive relationship between the data analytics capabilities and supply chain performance in digital upstream supply chain procurement processes. The present study also clarifies the impact and role of data analytics capabilities in digital supply chain development and success.

The dynamic capabilities view is invoked to hypothesize relationships among the service supply chain management (SSCM) process capabilities using the information technology management (ITM) process capability. This study argues that ITM will have an impact on the service performance management (SPM) process capability only when it works through mediators and demonstrates the impact by using the framework of SSCM process capabilities.

This study is based on a survey using quantitative data collection to empirically test the research framework. The proposed framework and hypotheses were tested using a mail-in survey of the service industry in Thailand. The statistical analysis of data acquired from the survey was performed using structural equation modeling.

The results support the existence of a mediating role for the ITM process affecting the SPM process. This study identifies the role of ITM and emphasizes the urgent need for firms to embed other mediating factors into their approaches to achieve SPM process goals in the service supply chain context.

The study offers important implications to researchers as well as practitioners by highlighting the significance of mediating roles for ITM to achieve SPM process.

This research is among the initial attempts to argue the impact of ITM on SPM through mediators.

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.

Part I of this chapter applies the principles of the philosophy of science and the derived scientific method to analyze the foundational concepts and core proposition of the Resource-Base View (RBV) as popularized by Barney (1986, 1991, 1997). This analysis identifies seven fundamental conceptual deficiencies and logic problems in Barney's conceptualization of “strategically valuable resources” and in Barney's VRIO framework for identifying strategically valuable resources that can be sources of sustained competitive advantage. Three problems – the Value Conundrum, the Tautology Problem in the Identification of Resources, and the Absence of a Chain of Causality – relate to the RBV's and VRIO's failure to provide an adequate conceptual basis for identifying strategically valuable resources. The Uniqueness Dilemma, the Cognitive Impossibility Dilemma, and an Asymmetry in Assumptions about Resource Factor Markets result in an inability of the VRIO framework to support identification of resources that can be sources of sustained competitive advantage. More fundamentally, the core proposition of the RBV – that resources that are strategically valuable, rare, inimitable, and organizationally embedded are sources of sustainable competitive advantage – is argued to result directly in the Epistemological Impossibility Problem that precludes use of the scientific method in RBV research. This chapter argues that until these conceptual deficiencies and logic problems are recognized and remedied, the RBV – in spite of its current popularity – is and will remain theoretically sterile and incapable of contributing in any systematic way to the development of strategy theory.

Part II of this chapter then suggests how foundational concepts developed within the competence perspective on strategy provide essential remedies for the identified deficiencies and problems in the RBV – and thereby provide a more conceptually adequate basis for representing the nature of firms in the scientific study of their interactions and competitive outcomes.

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.

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.

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.