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Service-oriented architecture is an emerging software architecture, in which web service (WS) plays a crucial role. In this architecture, the task of WS composition and verification is required when handling complex requirement of services from users. When the number of WS becomes very huge in practice, the complexity of the composition and verification is also correspondingly high. In this paper, the authors aim to propose a logic-based clustering approach to solve this problem by separating the original repository of WS into clusters. Moreover, they also propose a so-called quality-controlled clustering approach to ensure the quality of generated clusters in a reasonable execution time.

The approach represents WSs as logical formulas on which the authors conduct the clustering task. They also combine two most popular clustering approaches of hierarchical agglomerative clustering (HAC) and k-means to ensure the quality of generated clusters.

This logic-based clustering approach really helps to increase the performance of the WS composition and verification significantly. Furthermore, the logic-based approach helps us to maintain the soundness and completeness of the composition solution. Eventually, the quality-controlled strategy can ensure the quality of generated clusters in low complexity time.

The work discussed in this paper is just implemented as a research tool known as WSCOVER. More work is needed to make it a practical and usable system for real life applications.

In this paper, the authors propose a logic-based paradigm to represent and cluster WSs. Moreover, they also propose an approach of quality-controlled clustering which combines and takes advantages of two most popular clustering approaches of HAC and k-means.

The purpose of this paper is to present a modified failure mode and effects analysis (FMEA) in order to make the assignment of the scores for the occurrence factor more robust, and to link the FMEA chart directly to the maintenance activities.

A well-known clustering algorithm (i.e. K-means), along with a normalisation approach, are applied and compared for the assignment of the occurrence scores. Subsequently, the relationship between failures and maintenance operations is made explicit by a correlation matrix. Finally, the K-means algorithm is applied to the maintenance operations again in order to sort them into priority classes.

It is found that this revised FMEA approach improves the standard one due to its more rigorous mathematical formulation and lean applicability in real operating environments.

The novel approach may be improved by a deeper statistical analysis and/or applying the fuzzy theory.

A real case study is introduced in order to show the applicability of this approach to the quality control of a blow moulding process. It is found that this approach reveals a high potentiality for dealing with real issues.

The paper provides a further step towards bridging the gap between theory and practical application of the FMEA approach.

The Indonesian government has been trying to support the development of small and medium enterprises (SMEs) in the country, as these enterprises are expected to play a crucial role not only for employment creation but also for GDP formation and export development. The paper aims to address the following three questions. First, are networks important for the development of SME clusters, especially for those involved in export activities? Second, in what type of clusters are networks well developed? Third, what is the role of government; does it also play as an important network for SME cluster development?

This paper is based on an ongoing research on the importance of networks in the development of export‐oriented SME clusters in Indonesia. Although the paper also discusses other important issues related to the development of SMEs in the country, i.e. constraints facing the enterprises and women entrepreneurs, the paper focuses on the importance of networks.

First, SMEs are of overwhelming importance to Indonesia because they account for more than 90 percent of all firms outside of the agricultural sector. Second, the main constraints faced by small entrepreneurs are, lack of finance and difficulties in marketing. Third, the representation of women entrepreneurs in Indonesia is still relatively low which can be attributed to various factors, e.g. low level of education and lack of training opportunities that make Indonesian women severely disadvantaged in both the economy and society. Finally, although in general Indonesia is not well represented with small and medium industrial clusters that feed into global commodity chains, some clusters have gradually become export‐oriented. Among many factors, well developed networks especially with traders, trading houses, and foreign tourists are indeed an important factor for their increasingly export activities. Even these agents have played more important role than supports from government for their successful export.

The paper examines the importance of networks for the export‐oriented SME clusters in Indonesia.

The purpose of this paper is to explore and describe research presented in the International Journal of Quality & Reliability Management (IJQRM), thereby creating an increased understanding of how the areas of research have evolved through the years. An additional purpose is to show how text mining methodology can be used as a tool for exploration and description of research publications.

The study applies text mining methodologies to explore and describe the digital library of IJQRM from 1984 up to 2014. To structure and condense the data, k-means clustering and probabilistic topic modeling with latent Dirichlet allocation is applied. The data set consists of research paper abstracts.

The results support the suggestion of the occurrence of trends, fads and fashion in research publications. Research on quality function deployment (QFD) and reliability management are noted to be on the downturn whereas research on Six Sigma with a focus on lean, innovation, performance and improvement on the rise. Furthermore, the study confirms IJQRM as a scientific journal with quality and reliability management as primary areas of coverage, accompanied by specific topics such as total quality management, service quality, process management, ISO, QFD and Six Sigma. The study also gives an insight into how text mining can be used as a way to efficiently explore and describe large quantities of research paper abstracts.

The study focuses on abstracts of research papers, thus topics and categories that could be identified via other journal publications, such as book reviews; general reviews; secondary articles; editorials; guest editorials; awards for excellence (notifications); introductions or summaries from conferences; notes from the publisher; and articles without an abstract, are excluded.

There do not seem to be any prior text mining studies that apply cluster modeling and probabilistic topic modeling to research article abstracts in the IJQRM. This study therefore offers a unique perspective on the journal’s content.

This papers aims to deal with enterprise networks and clusters dynamics, as well as inter‐firm joint efforts and collaborations, in order to study their evolution and possible effects when radical innovation occurs inside them.

In order to study these dynamics, with the optimal balancing among different strategies and the importance of exogenous parameters in cluster creation, a model is presented. It follows the agent‐based paradigm, particularly suited for describing complex social systems in which many parts interact among them. This allows one to create simulations of the studied system, and to test different hypotheses. Besides, it is the only paradigm in which the emergent features of complex systems can arise spontaneously, thanks to the bottom‐up design. A model is introduced and described in detail.

Qualitative results are described, reflecting current state‐of‐the art theories. The results show how clusters emerge and evolve among enterprises, and how radical innovation can trigger this phenomenon. Different managerial behaviour (externally or internally focused) is discussed as well.

The most important feature of a model based on agent is the possibility of repeating the experiment several times, by changing one or few variables at a time, by leaving the others unchanged. It constitutes for social sciences the equivalent of lab experiments for such disciplines as physics or chemistry. The presented model allows the study of different clustering scenarios, by changing the initial conditions.

This study aims to investigate the organizational learning of trainee auditors who represent the young generation of new entry-level professionals in CPA firms, and examines the possible associations between organizational learning and job satisfaction.

A questionnaire survey is administered among the target group of trainee auditors to explore possible approaches to their organizational learning in CPA firms. The results are used to generate organizational learning variables, which enable us to empirically test the research hypotheses regarding the association between organizational learning and job satisfaction.

The authors conclude that there are three main dimensions of organizational learning for new entry-level professionals in CPA firms, namely: workplace interactions, supervising and monitoring and supportive informational systems. The authors also find that workplace interactions and supportive information systems are significantly associated with job satisfaction. The authors show that the females and males prefer different approaches to organizational learning in CPA firms. The authors also find that trainee auditors who work for bigger CPA firms enjoy more job satisfaction than those working for smaller CPA firms, and that male trainee auditors are more easily satisfied with audit jobs than female trainees.

This study is limited in that its sample is composed of trainee auditors, who are used to proxy for entry-level professionals in CPA firms. Future studies can include a direct focus on the organizational learning of junior auditors in CPA firms. Future studies can also investigate organizational learning in the firm-wide context in which CPA firms and their employees are considered as part of a larger situational process of organizational learning.

The conclusions can help to improve practice management and human resource policies in CPA firms. The findings highlight the importance of establishing an effective organizational learning culture, and suggest how this can be achieved by providing friendly and instructive workplace interactions, helpful supervisory and mentoring relationships, and better information support.

This study contributes to the audit literature by identifying the three dimensions of organizational learning for entry-level professionals in CPA firms. The authors substantiate the argument that mentor-protégé relationships in CPA firms have different effects on job satisfaction for female and male trainee auditors.

The purpose of this paper is to develop and implement methods for benchmarking the food safety and hygiene between retail outlets at the same time or at the same retail outlets at different times.

A tailor made questionnaire for the collection of food safety and hygiene remarks was designed to be applied in a large chain of retail outlets. The remarks were classified in the five categories of the Ishikawa model (materials, methods, personnel, equipment and environment). The retail outlets were located all over Greece and the audits were performed in a one-year term. Food safety experts were used as auditors after a six-month training period. The data collected were subject to analysis of the benchmarking scores and to cluster analysis to identify regions with similar food safety profiles.

Polar charts were used to illustrate the benchmarking scores for each of the five categories of evaluation per auditing period at the retail outlets. Another polar chart illustrates the benchmarking scores for each of the 12 regions of Greece. Cluster analysis demonstrates that some regions, like Ionian Islands and South Aegean, have similar profiles on food safety for the retail outlets.

The developed methodology can be used by retail companies with several outlets or by a group or an association of companies in order to identify problematic sectors and to set priorities while dealing with issues of food safety and hygiene. The work is limited to the Greek outlets but the methodology has potential application to every other country.

Deep learning (DL) technologies assist manufacturers to manage their business operations. This research aims to present state-of-the-art insights on the trends and ways forward for DL applications in manufacturing operations.

Using bibliometric analysis and the SPAR-4-SLR protocol, this research conducts a systematic literature review to present a scientific mapping of top-tier research on DL applications in manufacturing operations.

This research discovers and delivers key insights on six knowledge clusters pertaining to DL applications in manufacturing operations: automated system modelling, intelligent fault diagnosis, forecasting, sustainable manufacturing, environmental management, and intelligent scheduling.

This research establishes the important roles of DL in manufacturing operations. However, these insights were derived from top-tier journals only. Therefore, this research does not discount the possibility of the availability of additional insights in alternative outlets, such as conference proceedings, where teasers into emerging and developing concepts may be published.

This research contributes seminal insights into DL applications in manufacturing operations. In this regard, this research is valuable to readers (academic scholars and industry practitioners) interested to gain an understanding of the important roles of DL in manufacturing operations as well as the future of its applications for Industry 4.0, such as Maintenance 4.0, Quality 4.0, Logistics 4.0, Manufacturing 4.0, Sustainability 4.0, and Supply Chain 4.0.

The purpose of this study is to discover the factors affecting customer delight, satisfaction and dissatisfaction in fine dining experiences (FDEs).

Online user generated 2,585 reviews on TripAdvisor for 46 five-star hotel restaurants operating in Istanbul were analyzed with the latent Dirichlet allocation (LDA) algorithm.

LDA created nine, eight and seven topics for delight, satisfaction and dissatisfaction, respectively. The most salient topics for customer delight, satisfaction and dissatisfaction in FDEs are staff (17.3%), view (19%), and food quality (23%), respectively.

This study is one of the few studies investigating customer delight and satisfaction together. The study shows that FDEs can be analyzed with text mining techniques. Moreover, the study contributes to the literature on customer delight by adding staff topic as an antecedent.

The first goal of this research is to analyse the effects of lean production (LP) on the policy of human resource management (HRM). The second is to determine whether or not implementation of HRM practices associated with LP explains the differences in organizational performance between manufacturing plants.

The paper developed a questionnaire for data collection. Findings are presented from 76 establishments (79.17 per cent of the total sample) that specialise in single‐firing ceramic tiles in Spain.

Companies that make the most of LP practices are also those that take care to train workers in using these practices as well as improving their employment security. However, the same is not true for the pay for performance system. The combination of LP with HRM practices reduces inventory and boosts productivity but does not appear to affect the other performance variables analysed.

For certain variables very little variation was found between the plants in the samples. The data are cross‐sectional, so causality cannot be definitively determined.

This paper indicates the HRM practices associated with the LP and the results obtained. It can thus be used to help human resource and production departments in improving organizational performance.

The paper extends the work of other researchers by focusing on a sector and a country that have been very little studied to date. The sample consists of a set of plants that are fairly homogeneous, which facilitates the analysis of the relationships between the selected variables, while keeping other variables controlled.