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The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

This study aims to analyze the business process management (BPM) applicability to a destination country-brand of a Latin American developing country and present a new process model for it.

This is a qualitative exploratory study whose unit of analysis is the BPM applicability to the destination country-brand of a Latin American developing country. Primary data were obtained through in-depth interview with the developing country's tourism international promotion agency. The secondary data were government reports and research papers on country-brand studies. Data analysis was carried out using stakeholder business context model, architecture processes, pain/gain matrix and BPMN for modelling.

The results present a new process model for country-brand management to reduce existing barriers. Three steps were carried out: analysis and modelling of the current processes of country-brand management; presentation of the current processes' problems and analysis and modelling of future processes country-brand management.

A theoretical contribution is provided in the literature on processes and country-brands since no previous studies relate these concepts and present a process-oriented management analysis for country-brands.

The main practical contribution was to identify the country-brand management problems, propose solutions to them and generate a new process model for country-brands that can be used as a managerial tool for national tourism organizations to improve their brands.

The present study is original as it approaches the first analysis of country-brand development with an emphasis on its process management.

The current study probes the multi-dimensional link between total quality management (TQM) and knowledge management (KM) and investigates how different TQM's dimensions impacts KM processes and how this nexus impacts organizational performance (operational and financial performance) by considering KM as an intermediating variable between TQM and organizational performance.

Six TQM practices are taken from “Malcolm Baldrige National Quality Award”, namely leadership, customer focus, strategic planning, human resource management, process management and information and analysis; KM processes include knowledge creation, acquisition, sharing and application and organizational performance comprises operational and financial performance. The researcher put together data from different sized services and manufacturing firms, from small, to medium and large firms located in the United Kingdom (UK).

The results suggested that a positive correlation existed between TQM, KM and organizational performance. KM is also shown to have quite a strong and positive influence on firm operational and financial performance and partially mediates the relationship between TQM and corporate performance. Dimensional analysis indicates that leadership, strategic planning, customer focus and HRM have a significant positive impact on all KM process, while mixed results have been found for process management and information and analysis. The contextual analysis indicates that except for knowledge creation, TQM plays an equally significant role for the majority of manufacturing establishments and services firms.

The present research makes a significant contribution to the scarce literature on the relationship between TQM and KM (mainly at dimensional level), particularly in the context of the UK, and provides a detailed understanding of the relations between different TQM and KM dimensions, and how their relationship impacts on the operational and financial performance of different sizes of manufacturing and services firms.

Highlights

1. Total quality management (TQM) enhances firms' knowledge management (KM) capabilities

2. KM partially mediates the relationship between TQM and firms' performance

3. Leadership, customer focus and process management indicated insignificant impact on knowledge creation

4. TQM and KM are equally important for all sizes manufacturing and services firms

Total quality management (TQM) enhances firms' knowledge management (KM) capabilities

KM partially mediates the relationship between TQM and firms' performance

Leadership, customer focus and process management indicated insignificant impact on knowledge creation

TQM and KM are equally important for all sizes manufacturing and services firms

The aim of this study is to provide a holistic analysis of all possible maritime business logistics processes related to import and export shipments in a fuzzy environment through a case study of a maritime logistics company based on the as-is and to-be models within business process management (BPM).

The analyses considered the following perspectives: (i) in the stage of the process identification, the definition of the problem was carried out; (ii) in the stage of the process discovery, ocean department was divided into ocean export/import operation departments; ocean export/import operation were divided into freight collect/prepaid operation processes; ocean export/import logistics activity groups were broken down into sub-activities for freight collect/prepaid operation; the logistics activity groups and their sub-activities were defined; each sub-activity as either operation or documentation process group was classified; the durations of sub-activities were evaluated by decision-makers (DMs) as fuzzy sets (FSs); the monthly total jobs activities were estimated by DMs as FSs; the applied to monthly jobs activities of total shipments were estimated by DMs as FSs; the durations of each sub-activities were aggregated; the duration of the logistics activity groups and the sub-activities for per job were calculated; the cumulative workload of logistics activity groups and sub-activities were calculated; the duration of sub-activities for per job as operation or documentation departments were calculated, (iii) in the stage of the process analysis, cumulative ocean export/import workload as operation or documentation for freight collect/prepaid were calculated; duration of activity groups and sub-activities for per job as operation or documentation were calculated; cumulative workload activity groups and sub-activities as operation or documentation were calculated, (iv) in the stage of the process redesign, cumulative workload, process cycle time as operation and documentation group and required labor force were calculated; the process cycle time of the theoretical, the as-is model and the to-be model were calculated: (i) the theoretical minimum process cycle time without resource were calculated by the critical path method (CPM), (ii) the process cycle time of the as-is model perspective with the 1 person resource constraint and (iii) the process cycle time of the to-be model perspective with the 2-person resource constraint were calculated by the resource constrained project scheduling problem (RCPSP) method.

The methodology for analyzing the ocean department operation process was successfully implemented in a real-life case study. It is observed that the results of the to-be model can be applicable for the company. The BPM-proposed methodology is applicable for the maritime logistics industry in the present study; however, it can be applied to other companies in maritime logistics as well as other industries.

This study contributes to research using BPM methodology in maritime logistics. This is the first study the logistics process analyses were carried out in terms of including all operation processes for a company. All processes were analyzed by using BPM methodology in maritime logistics. This study demonstrated the application of the BPM as-is and to-be models to maritime logistics. The as-is and the to-be models of the BPM methodology were applied in maritime logistics.

This methodology applied in this study can enable organizations operating in the time-urgent maritime logistics sector to manage their logistics processes more efficiently, increase customer satisfaction, reduce the risks of customer loss due to poor operational performance and increase profits in the long term. Through the use of these methodologies utilizing FSs, the CPM and the RCPSP methods, this study is expected to make contributions to the BPM literature and provide original insights into the field. Furthermore, this study will undertake a comprehensive analysis of maritime logistics with respect to BPM to deliver noteworthy contributions to the maritime logistics literature and provide original perspectives into the field.

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.

Background: Most children in low-income countries complete their elementary education with low competency in essential reading, writing, and arithmetic skills. Besides, about 250 million students are not learning the basics, most of whom have spent at least four years in school, and this failure is coined the global learning crisis. This study aimed to examine educational quality management practices perceived by secondary school teachers.

Methods: The study employed a multilevel mixed-method design. Employing a simple random sampling technique, the researcher selected 251 teachers from 10 secondary schools in the research regions. He collected data through a researcher-designed questionnaire, school standards, and student achievement records from November 2018 to March 2019. He analyzed data from a questionnaire using frequency, percentage, mean, Pearson correlation, and exploratory factor analysis. The document review concerning quality management was analyzed using content analysis to triangulate the quantitative findings.

Results: At the school level, the study revealed the impracticality of laboratories. Besides, incompetent and unmotivated teachers and students ran the education business from the input side. At the same level, principals' management practices on staff development and encouraging parents to support their schools were low. The principals' management practices in the teaching-learning process were also undesirable at the classroom level. Overall, the study revealed incredibly insufficient input, process, and output management in the study context.

Conclusion: Hence, the study concluded that it is difficult to achieve the very objectives of producing creative, critical, and problem-solving individuals through this type of educational provision and its management. Due to this, it is not easy to achieve quality education for all goals.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

In the current scenario, cybersecurity issues have emerged to be a major challenge for firms to deal with. The increased use of technologies has increased radically the volume and typology of information produced, exchanged, and managed by firms thus creating conditions for cybersecurity incidents or information breaches. In this situation, it becomes paramount for firms to recognize cybersecurity risks and be prepared to prevent them through the implementation of approaches and technologies able to ensure a high level of protection.

In this chapter, we provide a framework for analyzing and managing cybersecurity risks. We employed a case study strategy to understand how the risk analysis process is carried out within an Information Security company. The study and observations obtained from this case study have permitted to define a framework useful for SME to deal with cybersecurity issues.

The purpose of this paper is to examine the contribution of big data in the transforming process of an IT firm to a learning organization.

The authors adopted a qualitative research approach to define and interpret the ideas and experiences of the IT firms’ employees and to present them to the readers directly. For this purpose, they followed a single-case study design. They researched on a small and medium enterprise operating in the IT sector in Düzce province, Turkey. This paper used a semi-structured interview and document analysis as data collecting methods. In all, eight interviews were conducted with employees. Brochures and website of the organization were used as data sources for the document analysis.

As a result of in-depth interviews and document analysis, the authors formed five main themes that describe perception of big data and learning organization concepts, methods and practices adopted in transforming process, usage areas of big data in organization and how the sample organization uses big data as a learning organization. The findings of this paper show that the sample organization is a learning IT firm that has used big data in transforming to learning organization and in maintaining the learning culture.

The findings contribute to literature as it is one of the first studies that examine the influence of big data on the transformation process of an IT firm to a learning organization. The findings reveal that IT firms benefit from the solutions of big data while learning. However, as the design of the research is single-case study, the findings may be specific to the sample organization. Future studies are required that examine the subject in different samples and by different research designs.

In literature, research on how IT firms’ managers and employees use big data in organizational learning process is limited. The authors expect that this paper will shed light on future research that examines the effect of big data on the learning process of the organization.

This systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.

Building upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.

This systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.

This study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.